Heterogeneity of intermittent smokers in a Hispanic college student sample

Accepted Manuscript Heterogeneity of intermittent smokers in a Hispanic college student sample

José Alonso Cabriales, Dylan K. Richards, Theodore V. Cooper PII: DOI: Reference:

S0306-4603(18)31514-4 https://doi.org/10.1016/j.addbeh.2019.04.028 AB 5970

To appear in:

Addictive Behaviors

Received date: Revised date: Accepted date:

31 December 2018 25 April 2019 25 April 2019

Please cite this article as: J.A. Cabriales, D.K. Richards and T.V. Cooper, Heterogeneity of intermittent smokers in a Hispanic college student sample, Addictive Behaviors, https://doi.org/10.1016/j.addbeh.2019.04.028

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José Alonso Cabriales, Ph.D. University of New Mexico-Gallup

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Heterogeneity of Intermittent Smokers in a Hispanic College Student Sample

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Dylan K. Richards, B.S. Theodore V. Cooper, Ph.D. The University of Texas at El Paso

Corresponding Author:

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Theodore V. Cooper, Ph.D. Department of Psychology The University of Texas at El Paso 500 W. University Ave. El Paso, TX 79968 USA Phone: (915) 747-6270 Fax: (915) 747-6553 E Mail: [email protected]

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Abstract Hispanics are more likely to be daily light smokers (DLS) and intermittent smokers (ITS) than non-Hispanic whites. Although daily light (≤ 10 cigarettes per day [CPD]) and intermittent (nondaily) smoking have increased in recent years, few studies have compared DLS and ITS,

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especially within a Hispanic sample. The primary aims of this study were to investigate

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differences between DLS and ITS, and within ITS, differences between converted ITS (CITS;

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previously smoked daily for ≥ 6 months) and native ITS (NITS; never smoked daily) in a Hispanic college student sample (Mage = 23.74, SD = 5.17; 58.1% male). Analyses were

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conducted using baseline data from a larger study that evaluated attitudes toward tobacco free

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campus policies in a U.S. university on the border with México. This study included data from 45 DLS and 216 ITS (CITS: n = 77, NITS: n =139; N = 261). Compared to DLS, ITS were

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younger (on average), less likely to identify as smokers, smoked on fewer days in the past

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month, smoked fewer cigarettes on smoking days, and reported less nicotine dependence. Compared to CITS, NITS were younger, less likely to self-identify as smokers, smoked on fewer

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days in the past month, smoked fewer CPD on smoking days, and were less dependent on

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nicotine. Given the similarities between current and past findings (suggesting that CITS are in between DLS and NITS—regarding smoking behavior), these data suggest a similar pattern

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likely exists also among Hispanic smokers. Additionally, the absence of some previously observed differences is relevant in characterizing this particular Hispanic college sample. These findings provide further insight for the tailoring of interventions that target Hispanic DLS, CITS and NITS). Keywords: smoking; daily light smokers; intermittent smokers; college students; Hispanics

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Heterogeneity of Intermittent Smokers in a Hispanic College Student Sample 1. Introduction Smoking is the leading cause of preventable death in the U.S. (Centers for Disease Control and Prevention [CDC], 2015). Although there has been variability in categorizing low

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level smokers (Okuyemi et al., 2002), several studies have referred to nondaily smokers as

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“intermittent” (Husten, 2009) and those smoking 10 or fewer cigarettes per day (CPD) as “daily

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light” smokers (Boulos et al., 2009; Fagan, Brook, Rubenstone, Zhang, & Brook, 2009). As such, we adopted these definitions. Despite recent decreases in the overall prevalence of

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smoking (CDC, 2015), the rates of daily light and intermittent smoking have increased (CDC,

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2018; Fish et al., 2014). Research has demonstrated the health consequences of smoking even at low levels, suggesting there is no safe level of smoking (Fish et al., 2014; Schane, Ling, &

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Glantz, 2010). Indeed, both light and intermittent smoking have been associated with increased

mortality (Sacks et al., 2012).

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rates of morbidity (e.g., cardiovascular and lung disease; Fish et al., 2014) and premature

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Intermittent / nondaily smoking increased between 2005 and 2014 from 19.2% to 23.2%

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nationally (percentages are proportions of all current smokers) (Jamal et al., 2015). Overall, an increased interest in studying these low-level smoking groups has been observed in the literature

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in recent years (e.g., Romero, Pulvers, Scheuermann, & Ahluwalia, 2014; Stennett, Krebs, Liao, Richie & Muscat, 2018; Sutfin et al., 2012). Research suggests that ethnic minorities are more likely to be daily light / intermittent smokers than non Hispanic whites (20.9% vs. 18.2% [proportions of all smokers]; Trinidad et al., 2011), which is indeed the case among Hispanic smokers (Cooper, Rodríguez de Ybarra, Charter, & Blow, 2011; Rodríguez-Esquivel, Cooper, Blow, & Resor, 2009). Although these patterns have recently become more common among

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smokers, few studies have investigated differences between daily light and intermittent smokers (e.g., Cooper et al., 2010; Shiffman et al., 2012b; Shiffman et al., 2014), especially among ethnic minorities. The patterns of daily light and intermittent smoking, which seem less biologically based and more psychosocially based (e.g., biopsychosocial model; Engel, 1980) somewhat

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conflict with the current understanding of tobacco smoking, which is theoretically predicated on

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the maintenance of nicotine levels in order to avoid withdrawal symptoms (Benowitz, 2010).

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Generally, compared to daily smokers (particularly among those who smoke >10 CPD), the smoking behavior of intermittent and daily light smokers is more strongly influenced by social

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factors / circumstances, and likely not driven primarily by nicotine addiction (e.g., Levy, Biener,

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& Rigotti, 2009; Robertson, Iousa, McGee, & Hancox, 2015; Shiffman, Kassel, Paty, Gnys, & Zettler-Segal, 1994). For example, Shiffman, Ferguson, Dunbar, and Scholl (2012a) found that

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intermittent smokers reported lower levels of nicotine dependence compared to daily smokers.

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Additionally, in a separate study, Shiffman and colleagues (2014) found that intermittent smoking was associated with behavioral / situational variables, such as alcohol use and

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socializing (i.e., interacting with others). Furthermore, Thrul, Buhler, and Ferguson (2014)

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found stimulus control to be significantly more salient for those who smoke ≤ 10 CPD compared to those who smoked at greater levels. From a clinical perspective, intermittent smokers engage

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in more quit attempts than daily light smokers (Shiffman et al., 2012a; Tindle & Shiffman, 2011), which by itself warrants the examination of relevant differences between these two groups of smokers. 1.1 Heterogeneity of intermittent smokers Furthermore, intermittent smokers have demonstrated considerable heterogeneity (e.g., Shiffman et al., 2012a; Shiffman et al., 2012b). More specifically, intermittent smokers have

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been further categorized as those who previously smoked daily for ≥ 6 months (i.e., converted ITS [CITS]) and those who have never smoked daily (i.e., native ITS [NITS]). Shiffman and colleagues (2012b) found that the smoking behavior of CITS was in between that of daily smokers and NITS. That is, CITS were heavier, more frequent, and more dependent than NITS,

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whereas daily smokers were observed as heavier, more frequent, and more dependent than CITS

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(Shiffman et al., 2012b). However, CITS still displayed some characteristics similar to those of

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daily smokers, suggesting some residual signs (e.g., addiction levels) of daily smoking. Additionally, compared to NITS, CITS were more likely to endorse drinking coffee as a smoking

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trigger, consume more caffeinated beverages (other than coffee) and less alcohol, and report

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lower income levels (Shiffman et al., 2012b). Indeed, these results (i.e., daily smokers being more dependent than intermittent smokers and, within intermittent smokers, CITS being more

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dependent than NITS) have been replicated by the same research team in a subsequent study

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which included multiple measures of nicotine dependence (Shiffman et al., 2012a). Notably, Shiffman, Dunbar, and Benowitz (2014) found that intermittent and daily smokers have similar

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nicotine metabolism rates, suggesting that differences in smoking patterns may not be accounted

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for biologically (although other differences [e.g., genetic] may exist). However, it was reported that among intermittent smokers, African Americans obtained more nicotine per cigarette than

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non Hispanic whites (Shiffman et al., 2014). This finding is consistent with previous research suggesting the heterogeneity among intermittent smokers which warrants a further examination among specific ethnic groups. It is of particular importance to study this group of low-level smokers since their tobacco use patterns have become more similar to those of users of other substances, who most of the time are nondaily users. Indeed, Shiffman (2009) noted that the recent increase of nondaily

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smoking is not surprising when considered in the context of other addictive behaviors. Particularly, tobacco is more likely to be used daily than other drugs (e.g., cocaine, alcohol), making nondaily patterns of tobacco use in a way somewhat consistent with typical use patterns (mostly behaviorally speaking) of other drugs (although there are important differences

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regarding drug effects, routes of administration, etc.) (Shiffman, 2009). Therefore, it is

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important to consider revising previous understandings of smoking behavior (and the

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maintenance of), mostly associated with nicotine dependence. Particularly, the “trough maintenance” paradigm (Russell, 1971)—smoking to maintain nicotine levels in order to avoid

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withdrawal symptoms—is likely not applicable to intermittent smokers. Understanding the

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characteristics of intermittent smokers and subgroups of them is important for informing potentially efficacious cessation interventions aimed at these groups of smokers. This study aims

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to assess differences between CITS and NITS among Hispanic smokers given that previous

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studies have focused on other samples / ethnocultural groups. This is of importance given that ethnic differences with respect to tobacco use do exist. To our knowledge, this is the first study

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to assess differences between CITS and NITS within a Hispanic sample; particularly in the

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context of the U.S. / Mexico border. 1.2 Study aims and hypotheses

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The primary aims of this study were to investigate differences between DLS and ITS in a sample of Hispanic college students. Among intermittent smokers, potential differences between CITS and NITS were also assessed. It was hypothesized that compared to CITS, NITS would report: younger age, having smoked on fewer days in the past month, fewer CPD (on smoking days), and lower nicotine dependence scores. 2. Method

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2.1 Participants and procedure Participants were 261 students (DLS = 45; ITS = 216 [CITS = 77, NITS =139]) from a large university located on the U.S. border with México (Mage = 23.74, SD = 5.17; 58.1% male). Intermittent smokers were defined as those who reported smoking 1-29 days in the past 30 days;

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daily light smokers were defined as those who reported smoking every day (30/30) in the past

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month and between 1 and 10 CPD. Tables 1 and 2 present relevant demographics for the total

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sample and subcategories of smokers.

Secondary analyses were conducted using baseline data collected from a larger study (see

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Cooper, Cabriales, Hernandez & Law, 2016) that evaluated attitudes toward tobacco free campus

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policies at a university on the U.S. border with México. A campus-wide email with the link to the online survey was sent to all faculty, staff, and students with a valid institutional email

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address approximately two years before the implementation of a tobacco free campus policy.

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Three emails were sent over the span of 3 – 4 months, capturing students enrolled in the Spring and Summer semesters. At the end of the study, participants were entered into a random drawing

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with a chance to win one of twenty $100 gift cards. Ethics approval for the study was obtained

2.2 Measures

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from the IRB at the University of Texas at El Paso.

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Sociodemographics. Typical sociodemographic information was collected. Included items assessed: gender, age, level of education, race / ethnicity, and income level. These same items have also been used in past studies, including the primary / parent study from where these data emanated (Cooper et al., 2016). Tobacco use. Past and current tobacco use behaviors were assessed (e.g., number of cigarettes smoked on smoking days, age of smoking initiation). Smoking status (smoker vs.

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nonsmoker) was determined based on the item “current smoking status” followed by these options: “Yes, I currently smoke,” “No, I quit within the last 6 months,” “No, I quit more than 6 months ago or have never smoked.” Those choosing the first option were categorized as current smokers. Intermittent smokers were further categorized as CITS or NITS; CITS were defined as

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those who reported having previously smoked daily for 6 months or more, and NITS were

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defined as those who reported never having smoked daily for 6 months or more.

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The Hooked on Nicotine Checklist (HONC; DiFranza et al., 2002). The HONC is a 10item measure that assesses loss of autonomy over tobacco use. The items (e.g., “Have you ever

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tried to quit, but couldn’t?”) are scored dichotomously (yes / no) and scores are computed by

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summing the number of affirmative responses. Research has found the HONC to be a more sensitive measure for assessing nicotine dependence among light and intermittent smokers,

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compared to other measures of nicotine dependence (Wellman et al., 2006). The HONC has

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demonstrated adequate reliability (α = .83) and validity in past research (Wellman et al., 2005), and, similarly, demonstrated adequate reliability in the present study (α = .88).

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The Short Acculturation Scale for Hispanics (SASH; Marín, Sabogal, VanOss, Otero-

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Sabogal, & Pérez-Stable, 1987). The SASH assesses level of acculturation to U.S. culture. This instrument has been found to have high internal reliability (α = .92; Marín et al., 1987), and

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internal reliability for our sample was found to be .904. Mean item scores are used for purposes of analyses and can range from one (indicating less acculturation) to five (indicating greater acculturation). 2.3 Approach to analysis Descriptive analyses were conducted to create profiles for daily light smokers, intermittent smokers, CITS, and NITS. Univariate analyses assessed the following comparisons:

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daily light smokers vs. intermittent smokers, NITS vs. daily light smokers, CITS vs. daily light smokers, and NITS vs. CITS; χ2 and t-tests were conducted for categorical and continuous variables, respectively. To correct for Type I error (α) inflation of multiple comparisons, we applied the Bonferroni correction to the significance threshold. Overall, 43 comparisons were

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made, and thus the correct significance threshold used was: α = .05/43 = 0.0012.

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A multivariate logistic regression assessed potential covariates associated with type of

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intermittent smoker (0 = NITS, 1 = CITS). Based on the recommendation of Hosmer, Lemeshow, and Sturdivant (2013), the univariate analyses for the NITS vs. CITS comparison

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informed which covariates would be included in the model, such that variables for the univariate

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tests with an associated p-value < .25 were entered simultaneously in the logistic regression. Per the parameters specified above, relevant comparisons (based on past research) were assessed,

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while including correlates that reached the mentioned p value. All analyses were conducted

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using SPSS 22 (IBM, 2013). 3. Results

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3.1 Daily light smokers compared to intermittent smokers

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Table 1 presents descriptive characteristics for daily light smokers, intermittent smokers, and the total sample, as well as univariate analyses comparing daily light and intermittent

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smokers. Compared to daily light smokers, intermittent smokers were, on average, more than two years younger than daily light smokers. While all daily light smokers identified as current smokers, slightly more than one quarter (25.5%) of intermittent smokers self-identified as nonsmokers, despite reporting having smoked at least once cigarette in the past 30 days. Additionally, intermittent smokers smoked fewer than half the CPD reported by daily light smokers and reported lower levels of nicotine dependence, as suggested by HONC scores.

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3.2 CITS and NITS compared to daily light smokers Table 2 presents descriptive characteristics for daily light smokers, CITS, and NITS, as well as univariate analyses for the following comparisons: daily light smokers vs. CITS, daily light smokers vs. NITS, and CITS vs. NITS. Additionally, CITS smoked on fewer daysand

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reported smoking fewer CPD. NITS were the group less likely to self-identify as current

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month, reported smoking fewer CPD, and lower HONC scores.

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smokers (66.9%). Compared to daily light smokers, NITS smoked on fewer days in the past

3.3 CITS compared to NITS

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Compared to CITS, NITS smoked less days in the past month, less CPD, and reported

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lower HONC scores. Indeed, as shown in Table 2, among all categories of smokers in this sample, NITS reported smoking the fewest number of days in the past month, fewest CPD, and

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the lowest HONC scores. See Table 2 for additional details.

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Table 3 presents the results of the multivariate logistic regression. With all variables considered simultaneously (variables for the univariate tests between CITS and NITS with an

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associated p-value < .25), only HONC scores were significantly associated with the likelihood of

4. Discussion

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being in the CITS category.

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4.1 Daily light smokers compared to intermittent smokers Overall, study results are somewhat consistent with relatively recent research reporting the heterogeneity of intermittent smokers using national longitudinal data (Wang, Sung, Yao, Lightwood, & Max, 2017). In this study, the greatest differences were observed between daily light and intermittent smokers. On average, intermittent smokers (compared to daily light smokers) were younger, less likely to self-identify as current smokers, and smoked fewer days in

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the past month. Indeed, the differences between daily light and intermittent smokers have been previously documented (Shiffman et al., 2012; Wang et al., 2017). One recent study (Shiffman & Terhorst, 2017) using ecological momentary assessment reported that intermittent smokers were more likely to smoke in the presence of smoking cues (e.g., alcohol, others present), which

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is consistent with the most common notions regarding light and intermittent smoking (Coggins,

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Murrelle, Carchman, & Heidbreder, 2009). Thus, intermittent smokers’ smoking behavior seems

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more influenced by social and environmental cues relative to daily light smokers and in Hispanic intermittent smokers is associated with a lower likelihood of self-identifying as smokers. This

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suggests that in the context of cessation interventions, strategies such as trigger management and

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enhancing stimulus control abilities are important to explore in Hispanic intermittent smokers. 4.2 CITS and NITS compared to daily light smokers

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Compared with daily light smokers, CITS were less likely to self-identify as current

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smokers, smoked on fewer days and fewer CPD, and reported lower HONC scores. NITS (also compared to daily light smokers) reported: younger age, smoking on fewer days in the past

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month, fewer CPD, and lower HONC scores. Consistent with past research (e.g., Scheuermann,

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Mburu, Mathur, & Ahluwalia, 2015) NITS were the group less likely to self-identify as current smokers. Nevertheless, some direct comparisons with findings from other studies were not

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feasible due to differing definitions of daily light smoking or instances in which heavier daily smokers (> 10 CPD) were included (e.g., Shiffman & Terhorst, 2017). Other researchers have also observed that lower-level smokers, particular NITS are less likely to self-identify as smokers, while heaver / more frequent smokers are more likely to endorse this “smoker” identity (Berg et al., 2011). 4.3 CITS compared to NITS

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Consistent with previous research (e.g., Shiffman et al., 2012a; 2012b), compared to NITS, CITS were older, heavier (smoked more CPD and smoked more frequently), and relatively more dependent smokers. Findings suggest that CITS may have intermediate levels of nicotine dependence in relation to daily light smokers and NITS (pointing toward residual signs

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of dependence among CITS). Also, NITS (compared with CITS) were younger and less likely to

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self-identify as current smokers. Among all sample smokers, NITS reported: smoking the

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fewest number of days in the past month (and fewest CPD), and the lowest HONC scores. Study findings suggest that in this sample nicotine dependence symptoms may be the best predictor of

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intermittent smoking status (i.e., CITS vs. NITS). Despite the overall somewhat consistent

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results with past studies regarding CITS and NITS, fewer significant differences between these two subgroups were observed in our sample of Hispanic smokers. Particularly, despite likely

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intuitive notions regarding ethnocultural differences (comparing our sample to previous

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samples), at least based on our findings; in this particular sample of smokers the variable most predictive of smoking status (CITS vs. NITS) was nicotine dependence score. Given the

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heterogeneity of intermittent smokers, more nuanced measurement tools (e.g., Flocke, Step,

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Lawson, Smith, & Zyzanski, 2016) may be warranted as a way to better assess smoking behavior (particularly nondaily smoking patterns), potential nicotine addiction symptoms and eventually

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provide tailored cessation interventions. Limitations and strengths Given the nature of these data, some study limitations may be noted. First, secondary analyses were conducted using data from a larger dataset, which limited the inclusion of cultural construct measures that may have informed the study and future directions further. The singular cultural construct included here was acculturation. While studies have demonstrated

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acculturation level differences between smokers and non-smokers in Hispanic college students (Cooper et al., 2011), these differences did not emerge among any of the subgroups of low level smokers, suggesting the inclusion of more nuanced Hispanic/Latinx constructs in future studies (e.g., generation status, familism, perceived microaggressions). Second, the cross-sectional

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nature of the study did not allow for the establishment of temporal precedence. Third, despite

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noted significant differences observed in this study, the effect sizes were mostly small (indeed,

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small variability was observed between CITS and NITS). However, current results were mostly consistent with previous research, and thus increase confidence in the validity of these findings.

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The primary strength of this study is that it is the first to compare CITS and NITS in a Hispanic

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college student sample. Additionally, although some previously noted associations were supported in this study; the absence of other significant associations suggests the potential

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uniqueness of intermittent smoking among Hispanic college students.

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Conclusion and future directions

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Given the increase in the prevalence of nondaily smoking as well as the low rate of successful quit attempts among ITS (e.g., Cooper et al., 2010), this study provides a further

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examination of nondaily smoking within a Hispanic college student sample. Indeed, the present

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findings were similar to the differences observed between these low-level smokers (e.g., daily light, intermittent) within other ethnocultural groups. This consistency of findings suggests that Hispanic low-level smokers may benefit from the same or similar interventions used with other ehtnocultural groups. Based on present findings, future directions include the assessment of further relevant psychosocial (and / or behavioral), more nuanced measurements of smoking and addiction and further cultural constructs that may further explain the smoking patterns of Hispanic CITS and NITS.

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Acknowledgements This work was funded by A Smoke Free Paso del Norte: An Initiative of the Paso del Norte Health Foundation Grant [26-8113-63A] awarded to Theodore V. Cooper. The funding source had no other role in the conduction of the research and/or the writing of the manuscript.

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The authors would like to acknowledge: members of the Prevention and Treatment in

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Clinical Health Lab, Nora Hernandez, and Annette Torres.

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References Benowitz, N. L. (2010). Nicotine addiction. New England Journal of Medicine, 362, 22952303.Berg, C. J., Nehl, E., Sterling, K., Buchanan, T., Narula, S., Sutfin, E., & Ahluwalia, J. S. (2011). The development and validation of a scale assessing individual

IP

Tobacco Research, 13, 1257–1265. doi:10.1093/ntr/ntr144

T

schemas used in classifying a smoker: Implications for research and practice. Nicotine &

CR

Boulos, D. N. K., Loffredo, C. A., El Setouhy, M., Abdel-Aziz, F., Israel, E., & Mohamed, M. K.

US

(2009). Nondaily, light daily, and moderate-to-heavy cigarette smokers in a rural area of Egypt: A population-based survey. Nicotine & Tobacco Research, 11, 134-138.

AN

Centers for Disease Control and Prevention [CDC]. (2015). Current Cigarette Smoking Among Adults in the United States—New York, June 26, 2003-June 30, 2004. MMWR, 56, 705-

M

708.

ED

Centers for Disease Control and Prevention [CDC]. (2018). Current Cigarette Smoking Among

PT

Adults--United States, 2016. MMWR, 67, 53-59. Coggins, C. R., Murrelle, E. L., Carchman, R. A., & Heidbreder, C. (2009). Light and

CE

intermittent cigarette smokers: a review (1989-2009). Psychopharmacology, 207, 343-

AC

363. doi:10.1007/s00213-009-1675-4 Cooper, T. V., Cabriales, J. A., Hernandez, N., & Law, J. (2016). A baseline assessment of attitudes toward tobacco free campus policies in a US/México border university. Addictive Behaviors, 60, 223-227. Cooper, T. V., Rodríguez de Ybarra, D., Charter, J. E., & Blow, J. (2011). Characteristics associated with smoking in a Hispanic college sample. Addictive Behaviors, 36, 13291332. doi:10.1016/j.addbeh.2011.07.021

ACCEPTED MANUSCRIPT HETEROGENEITY OF INTERMITTENT SMOKERS

17

Cooper, T. V., Taylor, T., Murray, A. A., DeBon, M. W., Vander Weg, M. W., Klesges, R. C., & Talcott, G. W. (2010). Differences between intermittent and light daily smokers in a population of U. S. Military recruits. Nicotine & Tobacco Research, 12, 465-473. doi:10.1093/ntr/ntq025

T

DiFranza, J. R., Savageau, J. A., Fletcher, K., Ockene, J. K., Rigotti, N. A., McNeill, A. D., ... &

IP

Wood, C. (2002). Measuring the loss of autonomy over nicotine use in adolescents: The

CR

DANDY (Development and Assessment of Nicotine Dependence in Youths) Study. Archives of Pediatrics & Adolescent Medicine, 156, 397-403.

US

Engel G. The clinical appplication of the biopsychosocial model. (1980). American Journal of

AN

Psychiatry, 137, 535–544.

Fagan, P., Brook, J. S., Rubenstone, E., Zhang, C., & Brook, D. W. (2009). Longitudinal

M

precursors of young adult light smoking among African Americans and Puerto Ricans.

ED

Nicotine & Tobacco Research, 11, 139-147. Fish, L. J., Pollak, K. I., Scheuermann, T. S., Cox, L. S., Mathur, C., & Ahluwalia, J. S. (2014).

PT

Comparison of native light daily smokers and light daily smokers who were former heavy

CE

smokers. Nicotine & Tobacco Research, 17, 546-551. doi:10.1093/ntr/ntu169 Flocke, S. A., Step, M. M., Lawson, P. J., Smith, S., & Zyzanski, S. J. (2016). Development of a

AC

measure of incremental behavior change toward smoking cessation. Nicotine & Tobacco Research. doi:10.1093/ntr/ntw217 Hosmer, D. W., Lemeshow, S., & Sturdivant, R. X. (2013). Applied Logistic Regression (3rd ed.). New York, NY: Wiley. Husten, C. G. (2009). How should we define light or intermittent smoking? Does it matter? Nicotine & Tobacco Research, 11, 111-121.

ACCEPTED MANUSCRIPT HETEROGENEITY OF INTERMITTENT SMOKERS

18

IBM Corp. (Released 2013). IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY: IBM Corp. Jamal, A., Homa, D. M., O’Connor, E., Babb, S. D., Caraballo, R. S., Singh, T…King, B. A. (2015). Current cigarette smoking among adults—United States, 2005-2014. MMWR, 64,

T

1233-1240.

IP

Levy, D.E., Biener, L., & Rigotti, N.A. (2009). The natural history of light smokers: A

CR

population-based cohort study. Nicotine & Tobacco Research, 11, 156-163. doi:10.1093/ntr/ntp011

US

Marín, G., Sabogal, F., VanOss, M. B., Otero-Sabogal, R., & Pérez-Stable, E. (1987).

AN

Development of a short acculturation scale for Hispanics. Hispanic Journal of Behavioral Sciences, 9, 183-205. doi: 10.1177/07399863870092005

M

Okuyemi, K. S., Harris, K, J., Scheibmeir, M., Choi, W. S., Powell, J., & Ahluwalia, J. S. (2002).

ED

Light smokers: Issues and recommendations. Nicotine & Tobacco Research, 4, S103S112.

PT

Robertson, L., Iosua, E., McGee, R., & Hancox, R. J. (2016). Nondaily, low-rate daily, and high-

CE

rate daily smoking in young adults: A 17-year follow-up. Nicotine & Tobacco Research, 18, 943-949.

AC

Rodriguez-Esquivel, D., Cooper, T. V., Blow, J. A., & Resor, M. R. (2009). Characteristics associated with smoking in a Hispanic sample. Addictive Behaviors, 34, 593-598. Romero, D. R., Pulvers, K., Scheuermann, T. S., & Ahluwalia, J. S. (2014). Psychosocial and behavioral characteristics among subgroups of nondaily college student smokers. Tobacco Use Insights, 7, 15-19. doi:10.4137/TUI.S13440 Russell, M. H. (1971). Cigarette smoking: Natural history of a dependence disorder. British

ACCEPTED MANUSCRIPT HETEROGENEITY OF INTERMITTENT SMOKERS

19

Journal of Medical Psychology, 44, 1-16. Sacks, R., Coady, M. H., Mbamalu, I. G., Johns, M., & Kansagra, S. M. (2012). Exploring the next frontier for tobacco control: Nondaily smoking among New York City adults. Journal of Environmental & Public Health, 2012. doi:10.1155/2012/14586

T

Schane, R.E., Ling, P.M., & Glantz, S.A. (2010). Health Effects of light and intermittent

CR

doi:10.1161/CIRCULATIONAHA.109.904235

IP

smoking: a review. Circulation, 121, 1518-1522.

Scheuermann, T. S., Mburu, W., Mathur, C., & Ahluwalia, J. S. (2015). Correlates of converted

US

and native nondaily smoking. Nicotine & Tobacco Research, 17, 1112-1119.

AN

doi:10.1093/ntr/ntu272

Tobacco Research, 11, 122-125.

M

Shiffman, S. (2009). Light and intermittent smokers: background and perspective. Nicotine &

ED

Shiffman, S., Dunbar, M. S., & Benowitz, N. L. (2014). A comparison of nicotine biomarkers and smoking patterns in daily and nondaily smokers. Cancer Epidemiology Biomarkers

PT

& Prevention, 23, 1264-1272.

CE

Shiffman, S., Dunbar, M.S., Li, X., Scholl, S.M., Tindle, H.A., Anderson, S.J., & Ferguson, S.G., (2014). Smoking patterns and stimulus control in intermittent and daily smokers.

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PLoS ONE 9, e89911. doi:10.1371/journal.pone.0089911 Shiffman, S., Ferguson, S. G., Dunbar, M. S., & Scholl, S. M. (2012a). Tobacco dependence among intermittent smokers. Nicotine & Tobacco Research, 14, 1372-1381. Shiffman, S., Paty, J. A., Kassel, J. D., Gnys, M., & Zettler-Segal, M. (1994). Smoking behavior and smoking history of tobacco chippers. Experimental and Clinical Psychopharmacology, 2, 126-142.

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Shiffman, S., Tindle, H., Li, X., Scholl, S., Dunbar, M., & Mitchell-Miland, C. (2012b). Characteristics and smoking patterns of intermittent smokers. Experimental and Clinical Psychopharmacology, 20, 264-277. Stennett, A., Krebs, N. M., Liao, J., Richie, J. P., Jr., & Muscat, J. E. (2018). Ecological

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momentary assessment of smoking behaviors in native and converted intermittent

IP

smokers. American Journal on Addictions, 27, 131-138. doi:10.1111/ajad.12690

CR

Sutfin, E. L., McCoy, T. P., Berg, C. J., Champion, H., Helme, D. W., O’Brien, M. C., & Wolfson, M. (2012). Tobacco use by college students: A comparison of daily and

US

nondaily smokers. American Journal of Health Behavior, 36, 218-229.

AN

doi:10.5993/AJHB.36.2.7

Thrul, J., Buhler, A., & Ferguson, S. G. (2014). Situational and mood factors associated with

M

smoking in young adult light and heavy smokers. Drug & Alcohol Review, 33, 420-427.

ED

doi:10.1111/dar.12164

Tindle, H.A. & Shiffman, S. (2011). Smoking cessation behavior among intermittent smokers

PT

versus daily smokers. American Journal of Public Health, 101, e1–e3.

CE

doi:10.2105/AJPH.2011.300186 Trinidad, D. R., Pérez-Stable, E. J., White, M. M., Emery, S. L., & Messer, K. (2011). A

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nationwide analysis of US racial/ethnic disparities in smoking behaviors, smoking cessation, and cessation-related factors. American Journal of Public Health, 101, 699706. doi:10.2105/AJPH.2010.191668 Wang, Y., Sung, H.Y., Yao, T., Lightwood, J., & Max, W. (2017). Infrequent and frequent nondaily smokers and daily smokers: Their characteristics and other tobacco use patterns. Nicotine & Tobacco Research. doi:10.1093/ntr/ntx038

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Wellman, R. J., DiFranza, J. R., Savageau, J. A., Godiwala, S., Friedman, K., & Hazelton, J. (2005). Measuring adults' loss of autonomy over nicotine use: The Hooked on Nicotine Checklist. Nicotine & Tobacco Research, 7, 157-161. Wellman, R. J., Savageau, J. A., Godiwala, S., Savageau, N., Friedman, K., Hazelton, J., &

T

DiFranza, J. R. (2006). A comparison of the Hooked on Nicotine Checklist and the

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Fagerström Test for Nicotine Dependence in adult smokers. Nicotine & Tobacco

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Table 1: Characteristics of intermittent and daily smokers ITS (n= 216) DLS (n= 45) Total (n= 261) n % N % n % Gender Χ2(1)= 1.63, p= .202 Male 120 56.3% 30 66.7% 150 58.1% Female 93 43.7% 15 33.3% 108 41.9% Income Χ2(4)= 3.85, p= .427 < $15,000 47 21.8% 5 11.1% 52 19.9% $15,000 to $30,000 65 30.1% 15 33.3% 80 30.7% $30,000 to $50,000 49 22.7% 12 26.7% 61 23.4% > $50,000 30 13.9% 5 11.1% 35 13.4% Prefer not to respond 25 11.6% 8 17.8% 33 12.6% Smoking identity (self-reported) Χ2(1)= 14.52, p <.001 Smoker 161 74.5% 45 100.00% 206 78.9% Non-smoker 55 25.5% 0 0.00% 55 21.1% Age smoking initiation Χ2(2)= 0.00, p= .998 ≤ 12 years of age 15 6.9% 3 6.7% 18 6.9% 13 - 17 years of age 110 51.0% 23 51.1% 133 51.0% ≥ 18 years of age 91 42.1% 19 42.2% 110 42.1% Menthol Χ2(1)= 0.51, p= .477 Yes 98 45.8% 18 40.0% 116 44.8% No 116 54.2% 27 60.0% 143 55.2% Continuous characteristics ITS DLS Total M(SD) M(SD) M(SD) Range Age 23.28(5.33) 25.95(6.92) 23.74(5.71) 18-59 t(255)= 2.87, p= .004 Days smoked 9.58(8.57) 30.00(0.00) 13.10(10.98) 1-30 t(259)= 15.95, p <.001 CPD 2.50(2.31) 5.73(2.60) 3.12(2.68) 1-19 t(232)= 8.24, p <.001 HONC score 2.24(2.46) 4.89(3.03) 2.71(2.76) 0-10 t(247)= 6.19, p <.001 SASH score 3.07(0.72) 3.27(0.76) 3.11(0.73) 1.17-4.89 t(259)= 1.60, p= .110 Note: ITS = Intermittent Smokers; DLS = Daily Light Smokers (reference condition); Days smoked = Number of smoking days in the past 30 days; CPD = Cigarettes per smoking day; HONC score = Hooked on Nicotine Checklist mean score; SASH score = Short Acculturation Scale for Hispanics’ mean score. Statistically significant differences after Bonferroni correction are in boldface.

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Table 2: Characteristics of native ITS, converted ITS and daily light smokers NITS (n= 139) CITS (n= 77) n % n % Gender Male Female Income

70 66

< $15,000 $15,000 to $30,000 $30,000 to $50,000 > $50,000 Prefer not to respond Smoking identity (self-reported)

29 42 30 20 18

Smoker Non-smoker Initiation age

93 46

≤ 12 years of age 13 – 17 years of age ≥ 18 years of age Menthol

8 69 62

Yes No e-cigarette use

65 73

Yes No Continuous characteristics Age

51.5% 48.5%

20.9% 30.2% 21.6% 14.4% 12.9%

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66.9% 33.1%

18 23 19 10 7

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5.8% 49.6% 44.6%

47.1% 52.9%

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DLS (n= 45) n % *Χ2(1)= 3.62, p= .057; **Χ2(1)= 3.16, p= .076; ***Χ2(1)= 0.04, p= .846

64.9% 35.1%

23.4% 29.9% 24.7% 13.0% 9.1%

30 15

88.3% 11.7%

45 0

11.1% 33.3% 26.7% 11.1% 17.8%

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66.7% 33.3%

*Χ2(4)= 1.06, p= .900; **Χ2(4)= 3.07, p= .546; ***Χ2(4)= 4.25, p= .374

*Χ2(1)= 11.96, p= .001; **Χ2(1)= 19.86, p < .001; ***Χ2(1)= 5.68, p= .017 100.00% 0.00% *Χ2(2)= 1.49, p= .475; **Χ2(2)= 0.11, p= .948; ***Χ2(2)= 0.38, p= .828

9.1% 53.2% 37.7%

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6.7% 51.1% 42.2% *Χ2(1)= 0.27, p= .605; **Χ2(1)= 0.69, p= .406; ***Χ2(1)= 0.14, p= .713

33 43

43.4% 56.6%

18 27

40.0% 60.0% *Χ2(1)= 1.71, p= .191; **Χ2(1)= 0.63, p= .427; ***Χ2(1)= 0.08 p= .773

10.9% 89.1% CITS M(SD) 24.14(4.93)

11 50 DLS M(SD) 23.74(5.71)

18.0% 82.0% Range 18-59

11 58

15.9% 84.1%

*t(211)= -1.77, p= .078; **t(179)= 3.10, p= .002; ***t(118)=1.67, p=.098

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Days smoked

7.76(7.66)

12.87(9.19)

13.10(10.98)

1-30

CPD

2.09(1.44)

3.17(3.15)

3.12(2.68)

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*t(214)= -4.37, p < .001; **t(182)= 19.45, p <.001; ***t(120)= 12.48, p < .001

*t(187)= -3.18, p= .002; **t(160)= 11.31, p <.001; ***t(115)= 4.57, p < .001 HONC score 1.42(1.90) 3.70(2.68) 2.71(2.76) 0-10 *t(203)= -7.10, p < .001; **t(173)= 8.91, p <.001; ***t(116)= 2.21, p= .029 SASH score 3.07(0.72) 3.09(0.74) 3.11(0.73) 1.17-4.89 *t(214)= -0.19, p= .851; **t(182)= 1.59, p= .113; ***t(120)= 1.28, p= .721 Note: NITS = Native Intermittent Smokers; CITS = Converted Intermittent Smokers; DLS = Daily Light Smokers; Days smoked = Number of smoking days in the past 30 days; CPD = Cigarettes per smoking day; HONC score = Hooked on Nicotine Checklist mean score; SASH score = Short Acculturation Scale for Hispanics’ mean score. * is NITS(1) v. CITS(2), ** is NITS(1) v. DLS(0), and *** is CITS(2) v. DLS(0). Statistically significant differences after Bonferroni correction are in boldface.

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Table 3: Logistic regression predicting smoking status among intermittent smokers (NITS v. CITS) B

S.E.

OR

p

OR 95% CI

Gender (Ref. is male) .355 .367 1.427 .333 .694 2.931 Smoking identity (Ref. is smoker) .774 .575 2.169 .178 .703 6.694 Age .032 .039 1.032 .413 .957 1.113 Days smoked .025 .026 1.026 .327 .975 1.079 CPD .068 .095 1.070 .476 .888 1.290 HONC score .340 .084 1.405 .000 1.192 1.656 Note: NITS = Native Intermittent Smokers; CITS = Converted Intermittent Smokers; Days smoked = Number of smoking days in the past 30 days; CPD = Cigarettes per smoking day; HONC score = Hooked on Nicotine Checklist mean score. NITS(0) v. CITS(1); Model fit: Χ2(6)= 41.80, p <.001; Bold denotes p < .001

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Hispanic and low level smokers warrant research focus. Significant differences were observed between daily light and intermittent smokers. Significant differences were observed between native and converted intermittent smokers. Differences observed among smoking categories may enhance cessation interventions.

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