Background. Personal smoke-free policies (home and vehicle) reduce secondhand smoke exposure, improve health, and increase quitting among smokers. Overall, 83.0% and 78.1% of Americans report smoke-free homes and vehicles, respectively. However, little is known about such policies among 2-year community college (CC) students, who represent a large, diverse population with higher smoking rates and less negative attitudes toward smoking than 4-year college students. Methods. Prevalence of, and factors associated with, personal smoke-free policies were examined for 2,475 CC smokers enrolled in a national trial of web-assisted tobacco intervention. Results. Few students had smoke-free home policies (20.7%), smoke-free vehicles (17.0%), both smoke-free home and vehicle policy (4.2%), or any policy (home or vehicle; 31.2%). In logistic regression models, having children was associated with a smoke-free home or any policy but not with a smoke-free vehicle, and among participants who had children, only 20% reported a smoke-free home, and only 15% had a smoke-free vehicle. In addition, not living with other smokers, living with parents or roommates/siblings (vs. alone), smoking later than 30 minutes after awakening, believing that smoking affects the health of others, and confidence in quitting were associated with presence of a smoke-free home or any policy; no variables were significantly associated with presence of a smoke-free vehicle. Conclusions. CC students represent a priority population for intervention regarding smoke-free homes and vehicles. Such intervention can decrease exposure of others, including children, and potentially increase the likelihood of quitting in this high-risk population.

Smoke-free home and car policies significantly reduce secondhand smoke exposure and associated health consequences (U.S. Department of Health and Human Services, 2006). Furthermore, presence of smoke-free homes is associated with higher quit rates among tobacco users (Gilpin, White, Farkas, & Pierce, 1999; Hyland et al., 2009; Lee & Kahende, 2007; Mills, Messer, Gilpin, & Pierce, 2009) and possibly with decreased use of alternative tobacco products (Zhang, Martinez-Donate, Kuo, & Piper, 2016). Prevalence of personal smoke-free policies has increased over the past decades (Centers for Disease Control and Prevention [CDC], 2014; Cheng, Okechukwu, McMillen, & Glantz, 2015), with recent reports indicating that 83.0% of U.S. households have smoke-free home policies (CDC, 2014) and 78.1% have smoke-free vehicle policies (Kruger, Jama, Homa, Babb & King, 2015).

Despite this progress, disparities exist among various subgroups. Smokers are consistently less likely to have smoke-free homes (CDC, 2014; Cheng et al., 2015; Dozier et al., 2014; King, Dube, & Homa, 2013; Kruger et al., 2015) and cars (Cheng et al., 2015; Kruger et al., 2015) relative to nonsmokers. For example, in 2012-2013, among combustible tobacco users, only about half (53.7%) reported smoke-free homes and about one third (34.2%) reported smoke-free vehicles; Kruger et al., 2015). Presence of a young child in the home may attenuate this disparity (Berg, Lessard, et al., 2011; Nabi-Burza et al., 2012; Ossip et al., 2013), though at least one study found that presence of children was not associated with smoke-free vehicles (Cheng et al., 2015). Lower rates of smoke-free home and/or vehicle policies have also been found for younger adults (ages 18-24; King et al., 2013; Cheng et al., 2015) relative to older groups, those with lower (vs. higher) education levels (Cheng et al., 2015; King et al., 2013; Kruger et al., 2015), and those of lower (vs. higher) socioeconomic status (King, Hyland, Borland, McNeill, & Cummings, 2011).

Approximately 20.4 million Americans were enrolled in college in 2013 (U.S. Department of Education, 2016), with most (73%) in the 18 to 24 years age range (U.S. Department of Education, 2014), making this an important target population for addressing secondhand smoke exposure and personal smoking rules. Within this group, 2-year college (“community college” [CC]) students may be a particularly high-risk population for not having personal smoke-free policies. CC students comprise 42% (approximately 7 million) of all undergraduate students and represent a large population of minority, first-generation, low-income students (Kena et al., 2015; Ma & Baum, 2016). CC students are about one third to two times (1.36-1.96) more likely to smoke relative to 4-year college students (Berg, An, et al., 2011; CDC, 2016; Lenk et al., 2012; Sanem, Berg, An, Kirch, & Lust, 2009; VanKim, Nelson, Ehlinger, Lust, & Story, 2012), report less negative attitudes about smoking (Berg, An, et al., 2011), and are less supportive of smoke-free policies (Berg, Lessard, et al., 2011). They typically do not live on campus (VanKim et al., 2012), and thus their home smoking policies are not directly affected by smoke-free campus residence rules.

Although CC students are an important target population for tobacco use and personal smoke-free policies, they are an understudied population (Berg, An, et al., 2011; Hasman, Berryman, & McIntosh, 2013; Prokhorov et al., 2008), and most research has focused on 4-year college students. The current report provides data on prevalence of personal smoke-free policies among a large sample of CC student smokers, and examines factors associated with presence of smoke-free home and car policies.

Method Participants Participants were 2,475 CC students who consented to and completed a baseline survey for a trial of web assisted tobacco interventions. Eligibility criteria for the trial were the following: ≥18 years old, enrolled either part-time (1-11 credits) or full-time (≥12 credits) in a community college, smoke ≥5 cigarettes per week, and plan to quit within the next 3 months. In addition, as in our prior trials, participants who quit smoking within 7 days of completing the baseline survey were included if they met all other criteria, as they may have quit either during the enrollment process or in anticipation of joining. Finally, to qualify for the current analyses, participants were required to have answered the primary outcome survey items on smoke-free home and vehicle policies. Participants with missing observations for vehicle (n = 194), indoor smoking, (n = 7), home smokers area (n = 9), and type of home specified as other (n = 11) were excluded (final N = 2,475/2,696). Procedure Participants were recruited through CCs, initially in New York State (75.4% of sample; 74.4% of whom were from outside of New York City area), and later expanded to a total of 23 states nationally (n = 1-334 participants/state). Recruitment channels included CC emails, courseware postings, and other on-campus electronic postings, printed materials (e.g., flyers with tear-offs and QR codes, posters, table tent cards), face to face project presence on campuses (e.g., tables at health fairs), engagement with on-campus project “champions,” and a small number of earned or paid media events. Recruitment details are reported separately (McIntosh et al., 2017). Potential participants entered the study through a link to an electronic screening, consent, and survey application using REDCap® (https://redcap.urmc.rochester.edu/redcap/). Those who met eligibility criteria based on the screening were linked to a consent form to digitally record consent, and then entered the baseline survey. Potential participants who did not qualify were referred to other resources. All procedures were approved by the institutional review board (IRB) at the University of Rochester and by individual CC IRBs where required by the CC. Measures Demographic, tobacco use, and personal smoke-free policy data were drawn from the screener and baseline survey, based on prior literature and conceptual relationship with personal smoke-free policy outcomes. Demographic Items Demographic items included age (18-24 years, ≥25 years), sex (male, female), race (White, other), ethnicity (Hispanic, non-Hispanic), marital status (married/living with domestic partner, other), parental status (have ≥1 child, no children), living arrangements (live alone, with own family, with parents, with roommates or siblings), type of home (multi-unit [attached home, apartment, dorm], detached home/mobile home), student status (full-time [1-11 credits], part-time [≥12 credits]), and veteran status (yes, no). Tobacco Use Items Tobacco use items included daily smoker (yes, no), past 30 day e-cigarette use (yes, no), first cigarette of the day (≤30 minutes, >30 minutes), presence of other home smokers (“Are there smokers living with you?” Yes, no), belief that smoking affects the health of others (“My smoking can affect the health of others”: agree/strongly agree, disagree/strongly disagree/unsure), and self-efficacy for quitting (“How confident are you that you will be able to stop smoking completely this time? Rate this on a scale of 1 to 10, with 1 being ‘not at all confident’ and 10 being ‘extremely confident’”). Personal Smoke-Free Policies A smoke-free home policy was defined as no smoking is allowed and no one actually smokes in the home (Ossip et al. 2013): “Please tell us which best describes how cigarette smoking is handled in your home (home includes porches and balconies)” = “No one is allowed to smoke anywhere” versus all other (“Smoking is permitted in some places or at some times,” “Smoking is permitted anywhere,” “Don’t know”) + “How often does anyone smoke inside your home?” = “Never” versus all other (“Daily,” “Weekly,” “Monthly,” “Less than monthly,” “Don’t know”). Smoke-free vehicle was defined as have a vehicle + no smoking is allowed: “Please tell us which best describes how cigarette smoking is handled in your car” = “No one is allowed to smoke in my car” versus all other (“Special guests are allowed to smoke in my car,” “People are allowed to smoke in my car only if the windows are open,” “People are allowed to smoke in my car at any time,” “Don’t know”). In addition, open-ended responses to the question, “What do you think might make it difficult for you to quit at this time” were examined for all references to personal smoke-free policy content to provide qualitative examples of students’ experiences. Data Analysis The primary outcomes were student report of having a smoke-free home policy (total sample, N = 2,475), having a smoke-free vehicle policy (analyses run only for students who reported having a vehicle; N = 2,109, 85.2% of sample), and having any personal smoke-free policy (smoke-free home or smoke-free vehicle; total sample, N = 2,475). Presence of smoke-free home and car was reported descriptively but not modeled because of the relatively small sample reporting both (N = 89). Univariate analyses were conducted to provide descriptive data for the total sample (%, mean/standard deviation), followed by bivariate analyses (chi squares and t tests) to examine the relationship of individual variables to the three outcomes (smoke-free home, smoke-free vehicle, any personal smoke-free policy). Variables that significantly differed between presence and absence of a personal smoke-free policy for each of the outcomes at p ≤ .10 were considered as candidate variables for multivariable analyses. In addition, the models a priori included parental status (having ≥1 child vs. no children), based on prior work by our group and others (Berg, Lessard, et al., 2011; Nabi-Burza et al., 2012; Ossip et al., 2013), and state in which subject attended a CC (defined as either New York State (NYS; N = 1,875) versus all other or NYS, two other states with the largest number of participants (Illinois, N = 334; Kentucky, N = 108), and all other (n = 1-41/state). Multicollinearity was tested by the variance inflation factor (VIF range 1.02-1.5; no multicollinearity observed). Three final multivariable models were run using full model logistic regressions, one for each outcome, entering a uniform set of independent variables for all analyses. To preserve the number of participants in analyses, a “not applicable” (NA) category was created for variables with ≥10 missing values (for NA, parental status, n = 166; living arrangements, n = 158; sex, n = 36; smoking, n = 76). Data were analyzed using SAS® Version 9.3.

Results Table 1 presents subject characteristics for the entire sample. Overall, participants were nearly equally split between traditional (<25 years) and nontraditional (≥25 years) college age groups, about two thirds were women (64.7%), 29.5% were non-White, 11.3% were Hispanic, and 39.7% reported having one or more children. Most smoked daily (92.5%) and within 30 minutes of awakening (64.7%), nearly one third used e-cigarettes (30.9%), about half (51.9%) reported other household smokers, most agreed that smoking affects the health of others (90.8%), and participants overall were only somewhat confident about quitting (mean = 6.68 ± 2.07/10 rating). Table 1. Subject Characteristics (N = 2,475). View larger version Prevalence of personal smoke-free policies was low (see Table 1). Only about one fifth (20.7%) reported having a smoke-free home, 17.0% a smoke-free vehicle, and very few (4.2%) reported having both a smoke-free home and a smoke-free vehicle (among participants who owned a vehicle). About one third (31.2%) reported having any personal smoke-free policy, defined as reporting a smoke-free home or a smoke-free vehicle. Table 2 presents results of bivariate analyses of differences between presence and absence of a personal smoke-free policy using each of the three outcomes (home, vehicle, any). Higher confidence in quitting was significantly associated with presence of personal smoke-free policies across all three outcomes. In addition, younger age, male gender, non-White race, Hispanic ethnicity, not living alone, nondaily smoking, e-cigarette use, smoking more than 30 minutes after awakening, and absence of other home smokers were associated with presence of a home policy. Non-White race, Hispanic ethnicity, not living alone, nondaily smoking, e-cigarette use, smoking more than 30 minutes after awakening, and absence of other home smokers were significantly associated with any personal smoke-free policy. No variables other than confidence were significantly associated with presence of a smoke-free vehicle policy (p < .05 or less for all comparisons). This total set of variables, along with those with p < .10 and state in which subject attended a CC, were entered into the multivariable models. Table 2. Results of Bivariate Analyses for Smoke-Free Home, Smoke-Free Vehicle, Smoke-Free Home or Vehicle. View larger version Table 3 shows results of the multivariable logistic regression models, defining state as New York State versus non–New York State (results for the multistate runs are reported in the text). The Hosmer–Lemeshow chi-square was not significant (p > .23-.53 across models), indicating an adequate fit for the models. Variables associated with greater likelihood of having a smoke-free home policy were having children, living with parents or roommates/siblings versus alone, and not living with other home smokers; smoking within 30 minutes of awakening was associated with lower likelihood of having a smoke-free home policy. Variables associated with having any personal smoke-free policy (home or car) were having children, living with parents versus living alone, not living with other home smokers, believing smoking affects the health of others, and confidence in quitting; again, smoking within 30 minutes was associated with lower likelihood of any policy. None of the variables was associated with presence of a smoke-free vehicle, though odds ratios were generally in the same direction for variables significantly associated with smoke-free home or any policy. To further explore factors associated with smoke-free vehicles, a separate logistic regression was run entering only those variables significantly associated with smoke-free vehicle policy in bivariate analyses; again, none was significantly related to smoke-free vehicle policy in the multivariable analysis. New York State versus non–New York State was not associated with personal smoke-free policies in any runs. The multistate model showed the same pattern of significant findings and similar estimates, though “All Other States” had a higher odds of having a smoke-free vehicle policy relative to NYS (odds ratio = 1.68, 95% confidence interval = [1.10, 2.562]). Table 3. Logistic Regression Analyses of Factors Associated With Personal Smoke-Free Policies. View larger version When queried about barriers to quitting in an open-ended question, a total of 18 responses were identified with content relevant to home smoking and 29 related to smoking in vehicles. Open and axial coding (Strauss & Corbin, 2007) was conducted by a single coder and checked by a second coder for consistency, with 100% agreement. Responses are summarized in Table 4. Themes around home smoking were smoking while watching television, movies, or playing video games at home, being around others smoking in the home, and the fact that smoking was allowed in the home. Themes related to vehicle smoking were the behaviors of smoking while commuting to school and/or work, smoking while driving (in general), addiction, and stress reduction while driving. Table 4. Student Responses Regarding Barriers to Quitting Relevant to Home and Vehicle Smoking. View larger version

Acknowledgements The authors express their appreciation to the community colleges who participated in this project. The authors also wish to acknowledge the following staff and undergraduate students who assisted with this project: D. Ververs, R. Block, K. Fogarty, E. Hancock, A. Kazimir, and E. Porter.

Authors’ Note

The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the National Cancer Institute or the National Institutes of Health, the funding agency.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Cancer Institute (R01CA152093).