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Actual and Perceived E-Cigarettes Behaviors among a National Sample of U.S. College Students

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Title: Actual and Perceived E-Cigarettes Behaviors among a National Sample of U.S. College Students
Language: English
Authors: Anas Khurshid Nabil (ORCID 0000-0002-9748-2426), Adam E. Barry (ORCID 0000-0001-6527-6866), Hye-Chung Kum (ORCID 0000-0002-6882-8053), Robert L. Ohsfeldt
Source: Journal of American College Health. 2024 72(1):109-117.
Availability: Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 9
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Smoking, Health Behavior, College Students, Drinking, Marijuana, Correlation, Student Attitudes, Peer Influence, Beliefs, Student Characteristics
DOI: 10.1080/07448481.2021.2024209
ISSN: 0744-8481
1940-3208
Abstract: Objective: Electronic cigarette use represents an important college health concern. This investigation assessed demographic and behavioral correlates associated with actual and perceived e-cigarette use among a national sample of American college students. Methods: Respondents (n = 19,861) comprised college students from over 40 distinct American higher education institutions. Multivariable logistic regression assessed whether (1) alcohol, tobacco or marijuana use were associated with e-cigarette use; (2) perceived peer use of alcohol, tobacco or marijuana were associated with perceived e-cigarette use. Results: Approximately 5% of survey respondents self-reported using e-cigarettes within the past month. More than 7 out of every 10 respondents, however, thought the 'typical student' was an e-cigarette user. As perceptions of typical student substance use increased, respondents were far more likely to contend the typical student used e-cigarettes. Discussion: In addition to adopting smoke-free campus policies, university officials should disseminate accurate information regarding e-cigarette behaviors of students.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1408423
Database: ERIC
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  Value: <anid>AN0174908847;acl01jan.24;2024Jan23.02:22;v2.2.500</anid> <title id="AN0174908847-1">Actual and perceived E-cigarettes behaviors among a national sample of U.S. college students </title> <p>Objective: Electronic cigarette use represents an important college health concern. This investigation assessed demographic and behavioral correlates associated with actual and perceived e-cigarette use among a national sample of American college students. Methods: Respondents (n = 19,861) comprised college students from over 40 distinct American higher education institutions. Multivariable logistic regression assessed whether (<reflink idref="bib1" id="ref1">1</reflink>) alcohol, tobacco or marijuana use were associated with e-cigarette use; (<reflink idref="bib2" id="ref2">2</reflink>) perceived peer use of alcohol, tobacco or marijuana were associated with perceived e-cigarette use. Results: Approximately 5% of survey respondents self-reported using e-cigarettes within the past month. More than 7 out of every 10 respondents, however, thought the 'typical student' was an e-cigarette user. As perceptions of typical student substance use increased, respondents were far more likely to contend the typical student used e-cigarettes. Discussion: In addition to adopting smoke-free campus policies, university officials should disseminate accurate information regarding e-cigarette behaviors of students.</p> <p>Keywords: actual use; campus policies; college students; electronic cigarettes; perceived use; vaping behavior</p> <hd id="AN0174908847-2">Introduction</hd> <p>College students in the United States, in particular, have been recognized as a high-risk population for vaping. Prevalence of e-cigarette use trend is exponentially on the rise, and major e-cigarette brands, such as Juul, have been increasingly gaining popularity among college students.[[<reflink idref="bib1" id="ref3">1</reflink>], [<reflink idref="bib3" id="ref4">3</reflink>], [<reflink idref="bib5" id="ref5">5</reflink>], [<reflink idref="bib7" id="ref6">7</reflink>]] Rates of vaping nicotine and vaping marijuana among college students doubled between 2017 and 2018. Specifically, from 2017 to 2018, the 30-day prevalence of vaping nicotine increased from 6.1% to 15.5%, and the 30-day prevalence of vaping marijuana rose from 5.2% to 10.9%.[<reflink idref="bib9" id="ref7">9</reflink>]</p> <p>While increased use of e-cigarettes among college students, in and of itself, is concerning, more than half (55%) of current college-aged Electronic Nicotine Delivery Systems (ENDS) users stated that they were also simultaneously using conventional tobacco products.[<reflink idref="bib1" id="ref8">1</reflink>] Among college students, there is a greater rate of acceptance of use and perception of acceptability of use of electronic cigarettes in public compared to smoking conventional cigarettes.[<reflink idref="bib10" id="ref9">10</reflink>] Further, a large contingent of college students represent "dual users," individuals who concurrently use tobacco cigarettes and electronic cigarettes. Dual-use undergraduate college students have longer smoking histories compared to regular tobacco smokers. Dual users also are more likely to exhibit higher frequencies of past quit attempts than other smoking groups.[<reflink idref="bib11" id="ref10">11</reflink>] Lee et al found that electronic cigarette use behavior was a negative predictor of smoking cessation attempts, and college students were less motivated to use e-cigarettes with the sole intention of utilizing it as a tool for the cessation of combustible cigarettes.[<reflink idref="bib12" id="ref11">12</reflink>] Moreover, dual-use college students have endorsed higher levels of positive smoking expectancies in contrast to regular smokers who use traditional cigarette products. Compared to non-users, dual users reported lower perceived harm and addictiveness of smoking e-cigarettes and cigarettes. Therefore, among college students, dual-use was associated to higher utilization of traditional tobacco cigarettes and e-cigarettes, and subsequently, nicotine dependence was related to excessive rates of heavy episodic drinking.[<reflink idref="bib1" id="ref12">1</reflink>],[[<reflink idref="bib11" id="ref13">11</reflink>], [<reflink idref="bib13" id="ref14">13</reflink>]]</p> <p>A longitudinal assessment of 3757 college students identified that e-cigarette use was associated with the onset of cigarette smoking behavior. Current and ever e-cigarette use raised nonsmokers chances of trying tobacco cigarettes in college/university students. Moreover, the same study asserts that male respondents and marijuana users were at a higher likelihood to initiate e-cigarette use than other college students.[<reflink idref="bib15" id="ref15">15</reflink>] Based on the extant literature, we hypothesized that persons who used other substances, such as alcohol and tobacco products, would be more likely to personally vape and also perceive more frequent e-cigarette use by peers.</p> <hd id="AN0174908847-3">Co-use of E-cigarettes along with alcohol, tobacco, and marijuana</hd> <p>In addition to being correlated with tobacco use, e-cigarette consumption is also linked to alcohol and marijuana use.[<reflink idref="bib1" id="ref16">1</reflink>],[<reflink idref="bib5" id="ref17">5</reflink>],[<reflink idref="bib7" id="ref18">7</reflink>],[[<reflink idref="bib16" id="ref19">16</reflink>], [<reflink idref="bib18" id="ref20">18</reflink>], [<reflink idref="bib20" id="ref21">20</reflink>], [<reflink idref="bib22" id="ref22">22</reflink>], [<reflink idref="bib24" id="ref23">24</reflink>]] Alcohol consumption, especially among students who engage in heavy episodic drinking (binge drinking), has been identified as a correlate to e-cigarettes use.[<reflink idref="bib1" id="ref24">1</reflink>],[<reflink idref="bib20" id="ref25">20</reflink>],[<reflink idref="bib25" id="ref26">25</reflink>] There is also growing prevalence of using marijuana via ENDS, with a large proportion of users reported vaping cannabis and mixed marijuana or marijuana derivatives (77.9%) such as, butane hash oil, hashish, dabs, wax, THC in e-cigarettes, followed by unknown/would not wish to share (16.4%), hookah (1.9%), herbs and supplements (1.9%), and other illicit substances (1.9%).[<reflink idref="bib24" id="ref27">24</reflink>] Among U.S. college students, alcohol drinking was associated with increased likelihood of alternative method for cannabis-vaping behavior and knowledge, such as, cannabis vape-pen use.[<reflink idref="bib26" id="ref28">26</reflink>]</p> <p>Among data from 482 college students at a large southwestern university, approximately 30% of all research participants had vaped nicotine, and 23% had vaped cannabis in the previous year.[<reflink idref="bib27" id="ref29">27</reflink>] Also, on the same study, respondents stated about more favorable attitudes and higher lifetime rates of vaping nicotine (37%) and vaping cannabis (29%). In terms of gender, men were more routinely vaping marijuana, compared to female respondents. Caucasian and Hispanic college respondents had a higher prevalence of vaping cannabis than African American, Asian, and other racial groups of students. Frequency of polysubstance use, such as tobacco cigarettes, nicotine vaping, marijuana, alcohol consumption, binge drinking, and other types of illicit drug use, such as cocaine and amphetamines, were associated with vaping cannabis among young adult college participants.[<reflink idref="bib27" id="ref30">27</reflink>] In contrast to females and other racial and ethnic groups, white male college students with a history of frequent alcohol and illicit drug consumption were more likely to report concurrent and simultaneous use of cannabis as well as both combustible and electronic cigarettes.[<reflink idref="bib28" id="ref31">28</reflink>] In most cases, college students used e-cigarettes when other substances, such as conventional tobacco products, marijuana, and alcohol were present during various socializing purposes, events and gatherings.[<reflink idref="bib16" id="ref32">16</reflink>],[<reflink idref="bib20" id="ref33">20</reflink>]</p> <hd id="AN0174908847-4">Demographic correlates associated with E-cigarette use among college students</hd> <p>Younger students perceive less vaping harm and have higher odds of current use or ever use of e-cigarettes.[<reflink idref="bib18" id="ref34">18</reflink>],[<reflink idref="bib20" id="ref35">20</reflink>],[<reflink idref="bib29" id="ref36">29</reflink>] In respect to gender, being a male college student is a significant risk factor for current e-cigarette use than females.[<reflink idref="bib1" id="ref37">1</reflink>],[<reflink idref="bib3" id="ref38">3</reflink>],[<reflink idref="bib15" id="ref39">15</reflink>],[<reflink idref="bib18" id="ref40">18</reflink>],[<reflink idref="bib20" id="ref41">20</reflink>],[<reflink idref="bib21" id="ref42">21</reflink>],[<reflink idref="bib30" id="ref43">30</reflink>] Compared to women (43.0%), men (57.0%) were more likely to report an increasing trend of other substance use, other than nicotine, in e-cigarettes (OSUE).[<reflink idref="bib24" id="ref44">24</reflink>] E-cigarette use was more likely linked to Non-Hispanic Whites compared to Hispanic or other race and ethnicity student groups.[<reflink idref="bib3" id="ref45">3</reflink>],[<reflink idref="bib8" id="ref46">8</reflink>],[<reflink idref="bib18" id="ref47">18</reflink>],[<reflink idref="bib20" id="ref48">20</reflink>] Kenne et al identified that white (93.5%) student respondents were predominantly more likely to report OSUE (other substance use in e-cigarettes) than African Americans and other general student population at the university.[<reflink idref="bib24" id="ref49">24</reflink>] Lower undergraduate college students were about four times more inclined to be current e-cigarette users in comparison to upper undergraduates.[<reflink idref="bib3" id="ref50">3</reflink>] Students residing at on-campus residence locations had higher likelihood of using e-cigarettes compared to others who lived in off-campus housing.[<reflink idref="bib18" id="ref51">18</reflink>],[<reflink idref="bib31" id="ref52">31</reflink>] Members of collegiate fraternity and/or sorority groups are at a higher risk of electronic cigarette use, tobacco smoking, drinking alcohol, and other substance use behaviors.[<reflink idref="bib18" id="ref53">18</reflink>],[[<reflink idref="bib32" id="ref54">32</reflink>], [<reflink idref="bib34" id="ref55">34</reflink>]] Greek members appeared to be at higher risk for use of multiple tobacco products and were almost twice as likely to report cigarette smoking, waterpipe tobacco smoking, and e-cigarette use, compared to non-fraternity and non-sorority members.[<reflink idref="bib34" id="ref56">34</reflink>]</p> <hd id="AN0174908847-5">Current investigation</hd> <p>As the aforementioned research makes clear, vaping/e-cigarette use represents an important, timely public health issue among adolescents and young adults.[[<reflink idref="bib35" id="ref57">35</reflink>], [<reflink idref="bib37" id="ref58">37</reflink>], [<reflink idref="bib39" id="ref59">39</reflink>], [<reflink idref="bib41" id="ref60">41</reflink>]] This investigation sought to explore e-cigarette use among a national sample of U.S. college students. Specifically, we assessed demographic and behavioral correlates, including the co-use of other substances, associated with actual personal use and perceived peer use of e-cigarettes. While the majority of existing literature focuses on individual predictors for using e-cigarettes, this investigation identifies and compares risk factors for both actual and perceived vaping behavior among U.S. college students. An enhanced understanding of such factors is important considering vaping is a growing trend among American youth and young adults.[<reflink idref="bib37" id="ref61">37</reflink>],[<reflink idref="bib38" id="ref62">38</reflink>],[[<reflink idref="bib43" id="ref63">43</reflink>], [<reflink idref="bib45" id="ref64">45</reflink>], [<reflink idref="bib47" id="ref65">47</reflink>]]</p> <hd id="AN0174908847-6">Methods</hd> <p>This secondary data analysis examined the National College Health Assessment (NCHA) research survey data (Fall, 2015).[<reflink idref="bib48" id="ref66">48</reflink>] NCHA is a nationally recognized comprehensive assessment of college student health behaviors, habits, and perceptions in the U.S., organized and collected by the American College Health Association (ACHA). Data are gathered biannual (fall or spring), where respondents included randomly selected groups of undergraduate and graduate students. Participation in this survey is voluntary, and students may skip or refuse to answer any uncomfortable questions if they desire. Email contact information is automatically destroyed right after the submission of participants' survey responses. Therefore, data provided are de-identified and blinded, and no responses can be linked to individual students or academic institutions. Currently, NCHA is administered in a Web-based format. Colleges and universities determine when to participate and can self-select accordingly. Public health researchers and college health administrators can request access to survey data through ACHA.[<reflink idref="bib48" id="ref67">48</reflink>]</p> <p>Questions related to e-cigarette variables were first included in the Fall 2015 ACHA-NCHA survey (version IIc Web survey). Fall 2015 semester survey data, which provides feedback from 19,861 respondents, comprised undergraduate and graduate college students across more than 40 distinct public and private institutions of higher education. Institutions in the South accounted for 41% of the sample (n = 8,161), followed by institution in the West region (31%; n = 6,084), Northeast (20%; n = 3,966), and Midwest (8%; n = 1,650). Past month frequency of use was established for alcohol, tobacco, marijuana, and e-cigarettes (ATME). In addition to the personal frequency of use, perceived use among each substance was established by having respondents estimate the use of ATME (alcohol, tobacco, marijuana, and e-cigarettes) by the "typical student" at their institution. Therefore, our present research framework is a cross-sectional study.[<reflink idref="bib48" id="ref68">48</reflink>] The Institutional Review Board (IRB) Administration of Texas A&M University determined that this research does not involve human subjects, on December 03, 2019. Given e-cigarette use and perceived use was first assessed in 2015, it is important to use that data to establish a baseline understanding of actual and perceived use of e-cigarettes. By doing so, subsequent iterations of the NCHA can be explored to determine whether changes are occurring in American college student e-cigarette behaviors and perceptions.</p> <hd id="AN0174908847-7">Variables and measures</hd> <p> <emph>Actual e-cigarette use</emph> was assessed with the following question: "Within the last 30 days, on how many days did you use E-cigarettes?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Based on participant responses, three categories were established: current users (1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily); ever users (have used, but not in last 30 days); and never users of e-cigarettes.</p> <p> <emph>Perceived e-cigarette use</emph> was assessed with the following question: "Within the last 30 days, how often do you think the typical student at your school used E-cigarettes?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Likewise, we recoded this existing variable into three categories: current users (1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily); ever users (have used, but not in last 30 days); and never users of e-cigarettes.</p> <p> <emph>Demographic Characteristics</emph> assessed included age, gender, year in school, race, current residence, Greek membership, while <emph>Behaviors & Perceptions</emph> included personal use of cigarettes, alcohol, and marijuana, and the perceived use of other substances among typical students.</p> <p> <emph>Actual Substance Use</emph>: Actual cigarette use was assessed with the following question: "Within the last 30 days, on how many days did you use Cigarettes?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Actual alcohol use was assessed with the following question: "Within the last 30 days, on how many days did you use Alcohol (beer, wine, liquor)?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Actual marijuana use was assessed with the following question: "Within the last 30 days, on how many days did you use Marijuana (pot, weed, hashish, hash oil)?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Responses from all three variables were recoded into three categories: current users (1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily); ever users (have used, but not in last 30 days); and never users.</p> <p> <emph>Perceived Substance Use</emph>: Perceived cigarette use was assessed with the following question: "Within the last 30 days, how often do you think the typical student at your school used Cigarettes?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Perceived alcohol use was assessed with the following question: "Within the last 30 days, how often do you think the typical student at your school used Alcohol (beer, wine, liquor)?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Perceived marijuana use was assessed with the following question: "Within the last 30 days, how often do you think the typical student at your school used Marijuana (pot, weed, hashish, hash oil)?" Response options included: never used, have used, but not in the last 30 days, 1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily. Responses from all three variables were recoded into three categories: current users (1–2 days, 3–5 days, 6–9 days, 10–19 days, 20–29 days, and used daily); ever users (have used, but not in last 30 days); and never users.</p> <hd id="AN0174908847-8">Data analysis</hd> <p>Descriptive statistics were used to characterize current users (vaped within the past 30 days), ever users (previously vaped, but not in the past 30 days), and never users of e-cigarettes, in terms of distributions of <emph>Demographics</emph> (age, gender, year in school, race, current residence, Greek membership) and <emph>Behaviors & Perceptions</emph> (personal use of cigarettes, alcohol, and marijuana; perceived use of other substances among typical student) as well as actual personal use and perceived peer use of electronic cigarettes. Two multivariable logistic regression models were calculated to assess (<reflink idref="bib1" id="ref69">1</reflink>) whether alcohol, tobacco or marijuana use were associated with the use of e-cigarettes; and (<reflink idref="bib2" id="ref70">2</reflink>) whether perceived use of alcohol, tobacco or marijuana by typical students were associated with perceived use of e-cigarettes, above and beyond the influence of several covariates (age, gender, year in school, race, current residence, Greek membership). The four primary race and ethnicity variables (White, Black, Hispanic, and Asian) were combined into mutually exclusive race and ethnicity categories. Descriptive statistics and multivariable logistic regression analyses predicting actual and perceived use of electronic cigarettes were conducted in STATA (version 15.0) software package.</p> <hd id="AN0174908847-9">Results</hd> <p></p> <hd id="AN0174908847-10">Descriptive statistics</hd> <p>Approximately 5% of respondents were classified as current e-cigarette users, while 85% never used. More than 7 out of every 10 respondents thought the 'typical student' on their campus was an e-cigarette user. Between perceived users of electronic cigarettes, respondents believed that 74% of their peers were currently habituated to vaping, whereas 16% never used.</p> <p>Table 1 provides frequency and percentage distributions comparing, actual, and perceived use of e-cigarettes. In Figure 1, approximately 5% report current, 11% ever, and 84% never actual personal use of electronic cigarettes. In contrast, also shown in Figure 1, approximately 74% report current, 10% ever, and 16% never perceived peer use of electronic cigarettes.</p> <p>PHOTO (COLOR): Figure 1. Percentage distribution assessing actual personal use and perceived peer use of electronic cigarettes (NCHA, Fall 2015).</p> <p>Table 1. Frequency and percentage distribution assessing actual and perceived use of electronic cigarettes (NCHA, Fall 2015).</p> <p> <ephtml> <table><thead><tr><td>Electronic cigarettes</td><td>Actual use N (%)</td><td>Perceived use N (%)</td></tr></thead><tbody valign="top"><tr><td>Current used</td><td>956 (4.9)</td><td>14,393 (73.7)</td></tr><tr><td>Ever used</td><td>2,077 (10.6)</td><td>2,018 (10.3)</td></tr><tr><td>Never used</td><td>16,631 (84.6)</td><td>3,107 (15.9)</td></tr><tr><td>Total</td><td>19,664 (100.0)</td><td>19,518 (100.0)</td></tr></tbody></table> </ephtml> </p> <p>Tables 2 and 3 provide descriptive statistics measures, including frequency and percentage distributions about current, ever, and never users, assessing actual and perceived use of e-cigarettes (See Tables 2 and 3).</p> <p>Table 2. Descriptive statistics assessing actual use of electronic cigarettes (NCHA, Fall 2015).</p> <p> <ephtml> <table><thead><tr><td>Variables</td><td>Actual use of electronic cigarettes</td></tr><tr><td>Current user N (%)</td><td>Ever user N (%)</td><td>Never user N (%)</td></tr></thead><tbody valign="top"><tr><td>Age groups (in years)</td></tr><tr><td char="."> 18–20</td><td char=".">583 (5.6)</td><td char=".">1,097 (10.6)</td><td char=".">8,693 (83.8)</td></tr><tr><td char="."> 21–23</td><td char=".">198 (4.1)</td><td char=".">551 (11.4)</td><td char=".">4,102 (84.6)</td></tr><tr><td char="."> 24–26</td><td char=".">56 (3.8)</td><td char=".">157 (10.7)</td><td char=".">1,249 (85.4)</td></tr><tr><td char="."> 27–29</td><td char=".">29 (3.2)</td><td char=".">102 (11.4)</td><td char=".">768 (85.4)</td></tr><tr><td> 30 and above</td><td char=".">83 (4.3)</td><td char=".">158 (8.2)</td><td char=".">1,676 (87.4)</td></tr><tr><td>Gender</td></tr><tr><td> Female</td><td char=".">471 (3.6)</td><td char=".">1,176 (9.0)</td><td char=".">11,392 (87.4)</td></tr><tr><td> Male</td><td char=".">482 (7.4)</td><td char=".">888 (13.7)</td><td char=".">5,117 (78.9)</td></tr><tr><td>Year in school</td></tr><tr><td> 1st year undergraduate</td><td char=".">317 (6.4)</td><td char=".">446 (9.0)</td><td char=".">4,198 (84.6)</td></tr><tr><td> 2nd year undergraduate</td><td char=".">202 (5.1)</td><td char=".">484 (12.2)</td><td char=".">3,298 (82.8)</td></tr><tr><td> 3rd year undergraduate</td><td char=".">194 (5.3)</td><td char=".">425 (11.7)</td><td char=".">3,020 (83.0)</td></tr><tr><td> 4th year undergraduate</td><td char=".">134 (4.5)</td><td char=".">341 (11.5)</td><td char=".">2,484 (84.0)</td></tr><tr><td> 5th year or more undergraduate</td><td char=".">49 (4.4)</td><td char=".">170 (15.3)</td><td char=".">891 (80.3)</td></tr><tr><td> Graduate or professional</td><td char=".">52 (2.0)</td><td char=".">185 (7.0)</td><td char=".">2,415 (91.1)</td></tr><tr><td>Race categories</td></tr><tr><td> White</td><td char=".">750 (5.3)</td><td char=".">1,608 (11.4)</td><td char=".">11,737 (83.3)</td></tr><tr><td> African-American</td><td char=".">36 (2.6)</td><td char=".">78 (5.7)</td><td char=".">1,253 (91.7)</td></tr><tr><td> Hispanic</td><td char=".">72 (4.3)</td><td char=".">195 (11.7)</td><td char=".">1,403 (84.0)</td></tr><tr><td> Asian</td><td char=".">61 (3.5)</td><td char=".">116 (6.7)</td><td char=".">1,560 (89.8)</td></tr><tr><td>Current residence</td></tr><tr><td> Off-campus</td><td char=".">524 (4.5)</td><td char=".">1,250 (10.8)</td><td char=".">9,797 (84.7)</td></tr><tr><td> On-campus</td><td char=".">428 (5.4)</td><td char=".">815 (10.2)</td><td char=".">6,716 (84.4)</td></tr><tr><td>Social fraternity or sorority membership</td></tr><tr><td> No</td><td char=".">789 (4.6)</td><td char=".">1,738 (10.2)</td><td char=".">14,590 (85.2)</td></tr><tr><td> Yes</td><td char=".">165 (6.9)</td><td char=".">325 (13.5)</td><td char=".">1,918 (79.7)</td></tr><tr><td>Other substance use</td></tr><tr><td>Cigarettes</td></tr><tr><td> Ever used</td><td char=".">209 (8.2)</td><td char=".">970 (38.2)</td><td char=".">1,362 (53.6)</td></tr><tr><td char="."> 1–2 days</td><td char=".">150 (22.3)</td><td char=".">221 (32.8)</td><td char=".">302 (44.9)</td></tr><tr><td char="."> 3–5 days</td><td char=".">71 (29.3)</td><td char=".">70 (28.9)</td><td char=".">101 (41.7)</td></tr><tr><td char="."> 6–9 days</td><td char=".">43 (26.2)</td><td char=".">47 (28.7)</td><td char=".">74 (45.1)</td></tr><tr><td char="."> 10–19 days</td><td char=".">62 (33.9)</td><td char=".">43 (23.5)</td><td char=".">78 (42.6)</td></tr><tr><td char="."> 20–29 days</td><td char=".">26 (25.2)</td><td char=".">29 (28.2)</td><td char=".">48 (46.6)</td></tr><tr><td> Used daily</td><td char=".">127 (24.1)</td><td char=".">144 (27.3)</td><td char=".">256 (48.6)</td></tr><tr><td> Never used</td><td char=".">268 (1.8)</td><td char=".">552 (3.6)</td><td char=".">14,400 (94.6)</td></tr><tr><td>Alcohol</td></tr><tr><td> Ever used</td><td char=".">88 (3.0)</td><td char=".">355 (12.1)</td><td char=".">2,499 (84.9)</td></tr><tr><td char="."> 1–2 days</td><td char=".">149 (4.3)</td><td char=".">357 (10.2)</td><td char=".">2,994 (85.5)</td></tr><tr><td char="."> 3–5 days</td><td char=".">166 (5.7)</td><td char=".">405 (13.8)</td><td char=".">2,355 (80.5)</td></tr><tr><td char="."> 6–9 days</td><td char=".">194 (7.8)</td><td char=".">398 (15.9)</td><td char=".">1,906 (76.3)</td></tr><tr><td char="."> 10–19 days</td><td char=".">208 (10.7)</td><td char=".">343 (17.7)</td><td char=".">1,391 (71.6)</td></tr><tr><td char="."> 20–29 days</td><td char=".">76 (12.8)</td><td char=".">105 (17.7)</td><td char=".">411 (69.4)</td></tr><tr><td> Used daily</td><td char=".">24 (11.1)</td><td char=".">51 (23.5)</td><td char=".">142 (65.4)</td></tr><tr><td> Never used</td><td char=".">47 (0.9)</td><td char=".">56 (1.1)</td><td char=".">4,906 (97.9)</td></tr><tr><td>Marijuana</td></tr><tr><td> Ever used</td><td char=".">247 (6.8)</td><td char=".">828 (22.9)</td><td char=".">2,547 (70.3)</td></tr><tr><td char="."> 1–2 days</td><td char=".">110 (10.2)</td><td char=".">231 (21.4)</td><td char=".">737 (68.4)</td></tr><tr><td char="."> 3–5 days</td><td char=".">81 (15.1)</td><td char=".">110 (20.6)</td><td char=".">344 (64.3)</td></tr><tr><td char="."> 6–9 days</td><td char=".">60 (19.6)</td><td char=".">76 (24.8)</td><td char=".">170 (55.6)</td></tr><tr><td char="."> 10–19 days</td><td char=".">74 (20.5)</td><td char=".">92 (25.5)</td><td char=".">195 (54.0)</td></tr><tr><td char="."> 20–29 days</td><td char=".">57 (21.2)</td><td char=".">76 (28.3)</td><td char=".">136 (50.6)</td></tr><tr><td> Used daily</td><td char=".">79 (20.1)</td><td char=".">136 (34.5)</td><td char=".">179 (45.4)</td></tr><tr><td> Never used</td><td char=".">245 (1.9)</td><td char=".">522 (4.0)</td><td char=".">12,274 (94.1)</td></tr></tbody></table> </ephtml> </p> <p>Table 3. Descriptive statistics assessing perceived use of electronic cigarettes (NCHA, Fall 2015).</p> <p> <ephtml> <table><thead><tr><td>Variables</td><td>Perceived use of electronic cigarettes</td></tr><tr><td>Current user N (%)</td><td>Ever user N (%)</td><td>Never user N (%)</td></tr></thead><tbody valign="top"><tr><td>Age groups (in years)</td></tr><tr><td char="."> 18–20</td><td char=".">7,758 (75.1)</td><td char=".">1,021 (9.9)</td><td char=".">1,555 (15.1)</td></tr><tr><td char="."> 21–23</td><td char=".">3,649 (75.4)</td><td char=".">467 (9.7)</td><td char=".">724 (15.0)</td></tr><tr><td char="."> 24–26</td><td char=".">1,020 (70.5)</td><td char=".">167 (11.5)</td><td char=".">260 (18.0)</td></tr><tr><td char="."> 27–29</td><td char=".">608 (68.5)</td><td char=".">115 (13.0)</td><td char=".">165 (18.6)</td></tr><tr><td> 30 and above</td><td char=".">1,264 (68.1)</td><td char=".">233 (12.6)</td><td char=".">359 (19.3)</td></tr><tr><td>Gender</td></tr><tr><td> Female</td><td char=".">9,852 (76.1)</td><td char=".">1,186 (9.2)</td><td char=".">1,904 (14.7)</td></tr><tr><td> Male</td><td char=".">4,451 (69.1)</td><td char=".">821 (12.7)</td><td char=".">1,171 (18.2)</td></tr><tr><td>Year in school</td></tr><tr><td> 1st year undergraduate</td><td char=".">3,659 (74.0)</td><td char=".">489 (9.9)</td><td char=".">794 (16.1)</td></tr><tr><td> 2nd year undergraduate</td><td char=".">2,905 (73.5)</td><td char=".">408 (10.3)</td><td char=".">642 (16.2)</td></tr><tr><td> 3rd year undergraduate</td><td char=".">2,779 (76.6)</td><td char=".">320 (8.8)</td><td char=".">527 (14.5)</td></tr><tr><td> 4th year undergraduate</td><td char=".">2,263 (76.7)</td><td char=".">277 (9.4)</td><td char=".">410 (13.9)</td></tr><tr><td> 5th year or more undergraduate</td><td char=".">842 (76.3)</td><td char=".">119 (10.8)</td><td char=".">143 (13.0)</td></tr><tr><td> Graduate or professional</td><td char=".">1,719 (66.2)</td><td char=".">363 (14.0)</td><td char=".">516 (19.9)</td></tr><tr><td>Race categories</td></tr><tr><td> White</td><td char=".">10,416 (74.4)</td><td char=".">1,543 (11.0)</td><td char=".">2,035 (14.5)</td></tr><tr><td> African-American</td><td char=".">986 (72.8)</td><td char=".">93 (6.9)</td><td char=".">276 (20.4)</td></tr><tr><td> Hispanic</td><td char=".">1,301 (78.0)</td><td char=".">140 (8.4)</td><td char=".">227 (13.6)</td></tr><tr><td> Asian</td><td char=".">1,134 (65.8)</td><td char=".">166 (9.6)</td><td char=".">424 (24.6)</td></tr><tr><td>Current residence</td></tr><tr><td> Off-campus</td><td char=".">8,453 (73.8)</td><td char=".">1,206 (10.5)</td><td char=".">1,801 (15.7)</td></tr><tr><td> On-campus</td><td char=".">5,858 (73.9)</td><td char=".">802 (10.1)</td><td char=".">1,269 (16.0)</td></tr><tr><td>Social fraternity or sorority membership</td></tr><tr><td> No</td><td char=".">12,462 (73.4)</td><td char=".">1,764 (10.4)</td><td char=".">2,750 (16.2)</td></tr><tr><td> Yes</td><td char=".">1,850 (76.7)</td><td char=".">242 (10.0)</td><td char=".">319 (13.2)</td></tr><tr><td>Other substance use</td></tr><tr><td>Cigarettes-typical student</td></tr><tr><td> Ever used</td><td char=".">706 (28.8)</td><td char=".">1,328 (54.1)</td><td char=".">419 (17.1)</td></tr><tr><td char="."> 1–2 days</td><td char=".">2,372 (84.0)</td><td char=".">256 (9.1)</td><td char=".">197 (7.0)</td></tr><tr><td char="."> 3–5 days</td><td char=".">2,639 (93.1)</td><td char=".">90 (3.2)</td><td char=".">107 (3.8)</td></tr><tr><td char="."> 6–9 days</td><td char=".">2,142 (93.4)</td><td char=".">71 (3.1)</td><td char=".">81 (3.5)</td></tr><tr><td char="."> 10–19 days</td><td char=".">2,307 (95.8)</td><td char=".">44 (1.8)</td><td char=".">58 (2.4)</td></tr><tr><td char="."> 20–29 days</td><td char=".">890 (95.3)</td><td char=".">22 (2.4)</td><td char=".">22 (2.4)</td></tr><tr><td> Used daily</td><td char=".">3,128 (95.5)</td><td char=".">59 (1.8)</td><td char=".">88 (2.7)</td></tr><tr><td> Never used</td><td char=".">200 (8.1)</td><td char=".">147 (5.9)</td><td char=".">2,129 (86.0)</td></tr><tr><td>Alcohol-typical student</td></tr><tr><td> Ever used</td><td char=".">67 (13.3)</td><td char=".">193 (38.3)</td><td char=".">244 (48.4)</td></tr><tr><td char="."> 1–2 days</td><td char=".">1,093 (63.6)</td><td char=".">250 (14.5)</td><td char=".">376 (21.9)</td></tr><tr><td char="."> 3–5 days</td><td char=".">1,431 (65.7)</td><td char=".">389 (17.9)</td><td char=".">359 (16.5)</td></tr><tr><td char="."> 6–9 days</td><td char=".">2,351 (69.8)</td><td char=".">509 (15.1)</td><td char=".">508 (15.1)</td></tr><tr><td char="."> 10–19 days</td><td char=".">4,396 (83.1)</td><td char=".">460 (8.7)</td><td char=".">437 (8.3)</td></tr><tr><td char="."> 20–29 days</td><td char=".">2,407 (91.2)</td><td char=".">116 (4.4)</td><td char=".">117 (4.4)</td></tr><tr><td> Used daily</td><td char=".">2,574 (93.9)</td><td char=".">80 (2.9)</td><td char=".">88 (3.2)</td></tr><tr><td> Never used</td><td char=".">47 (4.6)</td><td char=".">17 (1.7)</td><td char=".">964 (93.8)</td></tr><tr><td>Marijuana-typical student</td></tr><tr><td> Ever used</td><td char=".">483 (35.9)</td><td char=".">480 (35.7)</td><td char=".">381 (28.4)</td></tr><tr><td char="."> 1–2 days</td><td char=".">1,813 (69.5)</td><td char=".">441 (16.9)</td><td char=".">356 (13.6)</td></tr><tr><td char="."> 3–5 days</td><td char=".">2,114 (78.4)</td><td char=".">323 (12.0)</td><td char=".">261 (9.7)</td></tr><tr><td char="."> 6–9 days</td><td char=".">2,547 (84.0)</td><td char=".">276 (9.1)</td><td char=".">209 (6.9)</td></tr><tr><td char="."> 10–19 days</td><td char=".">3,087 (88.7)</td><td char=".">220 (6.3)</td><td char=".">174 (5.0)</td></tr><tr><td char="."> 20–29 days</td><td char=".">1,677 (91.5)</td><td char=".">95 (5.2)</td><td char=".">60 (3.3)</td></tr><tr><td> Used daily</td><td char=".">2,295 (94.6)</td><td char=".">55 (2.3)</td><td char=".">76 (3.1)</td></tr><tr><td> Never used</td><td char=".">323 (16.0)</td><td char=".">123 (6.1)</td><td char=".">1,572 (77.9)</td></tr></tbody></table> </ephtml> </p> <hd id="AN0174908847-11">Multivariable logistic regression model</hd> <p>We estimated multivariable logistic regression models for both actual and perceived use of electronic cigarettes. Multivariable logistic regression model results are shown in Tables 4 and 5. Table 4 provides multivariable logistic regression model predicting actual use of e-cigarettes (See Table 4). The multivariable logistic regression model (Table 4) predicting actual e-cigarette use demonstrates, in terms of gender, male students (OR = 2.28, p < 0.01) were at higher odds of vaping and 2.28 times more likely to use e-cigarettes compared to females. Both undergraduates and graduate or professional students demonstrated statistically significant results, more specifically, 2nd year (OR = 0.62, p < 0.01), 3rd year (OR = 0.49, p < 0.01), 4th year (OR = 0.43, p < 0.01), 5th year or more (OR = 0.33, p < 0.01) and graduate or professional (OR = 0.15, p < 0.01), however, older students seem less likely to use e-cigarettes in comparison to 1st-year undergraduates. African Americans (OR = 0.49, p < 0.01) and Hispanic/Latino (OR = 0.71, p < 0.05) student groups were less likely to use e-cigarettes compared to Whites.</p> <p>Table 4. Multivariable logistic regression model predicting actual use of electronic cigarettes (NCHA, Fall 2015).</p> <p> <ephtml> <table><thead><tr><td>Actual use</td><td>(1) Electronic cigarettes (N = 16,428)</td></tr></thead><tbody valign="top"><tr><td>Variables</td><td>Odds ratio (OR)</td><td char=".">95% Confidence interval (CI)</td></tr><tr><td><italic>Age groups (in years)</italic></td></tr><tr><td> 18–20</td><td>1.00</td><td>–</td></tr><tr><td> 21–23</td><td>0.76*</td><td>(0.571–1.010)</td></tr><tr><td> 24–26</td><td>0.72</td><td>(0.487–1.066)</td></tr><tr><td> 27–29</td><td>0.66*</td><td>(0.408–1.069)</td></tr><tr><td> 30 and above</td><td>0.80</td><td>(0.566–1.129)</td></tr><tr><td><italic>Gender</italic></td></tr><tr><td> Female</td><td>1.00</td><td>–</td></tr><tr><td> Male</td><td>2.28***</td><td>(1.942–2.672)</td></tr><tr><td><italic>Year in school</italic></td></tr><tr><td> 1st year undergraduate</td><td>1.00</td><td>–</td></tr><tr><td> 2nd year undergraduate</td><td>0.62***</td><td>(0.488–0.777)</td></tr><tr><td> 3rd year undergraduate</td><td>0.49***</td><td>(0.377–0.628)</td></tr><tr><td> 4th year undergraduate</td><td>0.43***</td><td>(0.306–0.607)</td></tr><tr><td> >4th year undergraduate</td><td>0.33***</td><td>(0.214–0.512)</td></tr><tr><td> Graduate or professional</td><td>0.15***</td><td>(0.100–0.232)</td></tr><tr><td><italic>Race categories</italic></td></tr><tr><td> White</td><td>1.00</td><td>–</td></tr><tr><td> African-American</td><td>0.49***</td><td>(0.331–0.721)</td></tr><tr><td> Hispanic</td><td>0.71**</td><td>(0.533–0.948)</td></tr><tr><td> Asian</td><td>0.92</td><td>(0.675–1.260)</td></tr><tr><td><italic>Current residence</italic></td></tr><tr><td> Off-campus</td><td>1.00</td><td>–</td></tr><tr><td> On-campus</td><td>1.00</td><td>(0.818–1.219)</td></tr><tr><td><italic>Social fraternity or sorority membership</italic></td></tr><tr><td> No</td><td>1.00</td><td>–</td></tr><tr><td> Yes</td><td>0.99</td><td>(0.795–1.244)</td></tr><tr><td><italic>Other substance use</italic></td></tr><tr><td><italic>Cigarettes</italic></td></tr><tr><td> Ever used</td><td>1.00</td><td>–</td></tr><tr><td> 1–2 days</td><td>2.08***</td><td>(1.574–2.756)</td></tr><tr><td> 3–5 days</td><td>3.02***</td><td>(2.051–4.446)</td></tr><tr><td> 6–9 days</td><td>2.46***</td><td>(1.541–3.940)</td></tr><tr><td> 10–19 days</td><td>3.34***</td><td>(2.172–5.142)</td></tr><tr><td> 20–29 days</td><td>4.01***</td><td>(2.271–7.088)</td></tr><tr><td> Used daily</td><td>3.10***</td><td>(2.281–4.221)</td></tr><tr><td> Never used</td><td>0.17***</td><td>(0.134–0.209)</td></tr><tr><td><italic>Alcohol</italic></td></tr><tr><td> Ever used</td><td>1.00</td><td>–</td></tr><tr><td> 1–2 days</td><td>1.46**</td><td>(1.067–1.984)</td></tr><tr><td> 3–5 days</td><td>1.80***</td><td>(1.316–2.450)</td></tr><tr><td> 6–9 days</td><td>1.78***</td><td>(1.299–2.438)</td></tr><tr><td> 10–19 days</td><td>1.84***</td><td>(1.333–2.539)</td></tr><tr><td> 20–29 days</td><td>1.80***</td><td>(1.194–2.711)</td></tr><tr><td> Used daily</td><td>1.74*</td><td>(0.947–3.189)</td></tr><tr><td> Never used</td><td>0.51***</td><td>(0.339–0.752)</td></tr><tr><td><italic>Marijuana</italic></td></tr><tr><td> Ever used</td><td>1.00</td><td>–</td></tr><tr><td> 1–2 days</td><td>1.20</td><td>(0.901–1.590)</td></tr><tr><td> 3–5 days</td><td>1.66***</td><td>(1.190–2.330)</td></tr><tr><td> 6–9 days</td><td>1.59**</td><td>(1.054–2.384)</td></tr><tr><td> 10–19 days</td><td>2.03***</td><td>(1.396–2.938)</td></tr><tr><td> 20–29 days</td><td>2.26***</td><td>(1.488–3.441)</td></tr><tr><td> Used daily</td><td>2.21***</td><td>(1.519–3.216)</td></tr><tr><td> Never used</td><td>0.48***</td><td>(0.386–0.598)</td></tr><tr><td> Constant</td><td>0.21***</td><td>(0.150–0.304)</td></tr></tbody></table> </ephtml> </p> <p>1 p < 0.01.</p> <ulist> <item>2 p < 0.05.</item> <item>3 p < 0.10.</item> </ulist> <p>Table 5. Multivariable logistic regression model predicting perceived use of electronic cigarettes (NCHA, Fall 2015).</p> <p> <ephtml> <table><thead><tr><td>Perceived use</td><td>(1) Electronic cigarettes – typical student (N = 16,378)</td></tr></thead><tbody valign="top"><tr><td>Variables</td><td>Odds ratio (OR)</td><td char=".">95% Confidence interval (CI)</td></tr><tr><td><italic>Age groups (in years)</italic></td></tr><tr><td> 18–20</td><td>1.00</td><td>–</td></tr><tr><td> 21–23</td><td>0.84</td><td>(0.650–1.084)</td></tr><tr><td> 24–26</td><td>0.76*</td><td>(0.547–1.051)</td></tr><tr><td> 27–29</td><td>0.71*</td><td>(0.491–1.041)</td></tr><tr><td> 30 and above</td><td>0.71**</td><td>(0.531–0.962)</td></tr><tr><td><italic>Gender</italic></td></tr><tr><td> Female</td><td>1.00</td><td>–</td></tr><tr><td> Male</td><td>1.11</td><td>(0.955–1.278)</td></tr><tr><td><italic>Year in school</italic></td></tr><tr><td> 1st year undergraduate</td><td>1.00</td><td>–</td></tr><tr><td> 2nd year undergraduate</td><td>0.87</td><td>(0.700–1.082)</td></tr><tr><td> 3rd year undergraduate</td><td>0.84</td><td>(0.660–1.059)</td></tr><tr><td> 4th year undergraduate</td><td>0.70**</td><td>(0.512–0.957)</td></tr><tr><td> >4th year undergraduate</td><td>0.89</td><td>(0.596–1.341)</td></tr><tr><td> Graduate or professional</td><td>0.51***</td><td>(0.369–0.697)</td></tr><tr><td><italic>Race categories</italic></td></tr><tr><td> White</td><td>1.00</td><td>–</td></tr><tr><td> African-American</td><td>0.42***</td><td>(0.323–0.543)</td></tr><tr><td> Hispanic</td><td>0.94</td><td>(0.727–1.218)</td></tr><tr><td> Asian</td><td>0.73***</td><td>(0.581–0.929)</td></tr><tr><td><italic>Current residence</italic></td></tr><tr><td> Off-campus</td><td>1.00</td><td>–</td></tr><tr><td> On-campus</td><td>0.86*</td><td>(0.721–1.017)</td></tr><tr><td><italic>Social fraternity or sorority membership</italic></td></tr><tr><td> No</td><td>1.00</td><td>–</td></tr><tr><td> Yes</td><td>0.92</td><td>(0.745–1.145)</td></tr><tr><td><italic>Other substance use</italic></td></tr><tr><td><italic>Cigarettes-typical student</italic></td></tr><tr><td> Ever used</td><td>1.00</td><td>–</td></tr><tr><td> 1–2 days</td><td>8.18***</td><td>(6.587–10.157)</td></tr><tr><td> 3–5 days</td><td>13.04***</td><td>(10.165–16.741)</td></tr><tr><td> 6–9 days</td><td>12.69***</td><td>(9.582–16.794)</td></tr><tr><td> 10–19 days</td><td>17.57***</td><td>(12.821–24.090)</td></tr><tr><td> 20–29 days</td><td>15.69***</td><td>(9.826–25.066)</td></tr><tr><td> Used daily</td><td>18.79***</td><td>(13.873–25.454)</td></tr><tr><td> Never used</td><td>0.13***</td><td>(0.102–0.157)</td></tr><tr><td><italic>Alcohol-typical student</italic></td></tr><tr><td> Ever used</td><td>1.00</td><td>–</td></tr><tr><td> 1–2 days</td><td>2.05***</td><td>(1.256–3.339)</td></tr><tr><td> 3–5 days</td><td>2.73***</td><td>(1.686–4.432)</td></tr><tr><td> 6–9 days</td><td>2.19***</td><td>(1.356–3.523)</td></tr><tr><td> 10–19 days</td><td>2.42***</td><td>(1.494–3.934)</td></tr><tr><td> 20–29 days</td><td>3.38***</td><td>(1.980–5.772)</td></tr><tr><td> Used daily</td><td>3.27***</td><td>(1.853–5.786)</td></tr><tr><td> Never used</td><td>0.58*</td><td>(0.308–1.081)</td></tr><tr><td><italic>Marijuana-typical student</italic></td></tr><tr><td> Ever used</td><td>1.00</td><td>–</td></tr><tr><td> 1–2 days</td><td>2.48***</td><td>(1.917–3.196)</td></tr><tr><td> 3–5 days</td><td>3.18***</td><td>(2.433–4.147)</td></tr><tr><td> 6–9 days</td><td>3.86***</td><td>(2.907–5.117)</td></tr><tr><td> 10–19 days</td><td>4.02***</td><td>(2.982–5.415)</td></tr><tr><td> 20–29 days</td><td>4.75***</td><td>(3.188–7.072)</td></tr><tr><td> Used daily</td><td>3.59***</td><td>(2.353–5.489)</td></tr><tr><td> Never used</td><td>0.39***</td><td>(0.287–0.522)</td></tr><tr><td> Constant</td><td>0.48***</td><td>(0.292–0.784)</td></tr></tbody></table> </ephtml> </p> <ulist> <item>4 p < 0.01.</item> <item>5 p < 0.05.</item> <item>6 p < 0.10.</item> </ulist> <p>Exposure-response relationships among cigarette, alcohol, and marijuana users were present, such that likelihood of current vaping increased significantly as substance use increased. Among self-reported personal cigarette smoker, current users, 1–2 days (OR = 2.08, p < 0.01); 3–5 days (OR = 3.02, p < 0.01); 6–9 days (OR = 2.46, p < 0.01); 10–19 days (OR = 3.34, p < 0.01); 20–29 days (OR = 4.01, p < 0.01) and used daily (OR = 3.10, p < 0.01) demonstrate statistical significance and positive odds relationships, hence, current cigarette users were more likely to use e-cigarettes compared to ever users. Among self-reported personal alcohol user, current users, 1–2 days (OR = 1.46, p < 0.05); 3–5 days (OR = 1.80, p < 0.01); 6–9 days (OR = 1.78, p < 0.01); 10–19 days (OR = 1.84, p < 0.01); 20–29 days (OR = 1.80, p < 0.01) and used daily (OR = 1.74, p < 0.10) demonstrate statistical significance and positive odds relationships, hence, current alcohol users were more likely to use e-cigarettes compared to ever users. Among self-reported personal marijuana user, current users, 3–5 days (OR = 1.66, p < 0.01); 6–9 days (OR = 1.59, p < 0.05); 10–19 days (OR = 2.03, p < 0.01); 20–29 days (OR = 2.26, p < 0.01) and used daily (OR = 2.21, p < 0.01) demonstrate statistical significance and positive odds relationships, hence, current marijuana users were more likely to use e-cigarettes compared to ever users.</p> <p>Table 5 reports results from a multivariable logistic regression model predicting perceived use of e-cigarettes (See Table 5). Multivariable logistic regression model (Table 5) predicting perceived e-cigarette use demonstrates, graduate or professional students (OR = 0.51, p < 0.01) are less likely to use e-cigarettes compared to first-year undergraduates. In terms of race, African Americans (OR = 0.42, p < 0.01) and Asian/Pacific Islander (OR = 0.73, p < 0.01) students are less likely to use e-cigarettes than Whites.</p> <p>Similarly, as perceptions of typical student substance use increased, respondents were far more likely to contend the typical student used e-cigarettes. Among respondents who perceived the typical student to be a current cigarette smoker, 1–2 days (OR = 8.18, p < 0.01); 3–5 days (OR = 13.04, p < 0.01); 6–9 days (OR = 12.69, p < 0.01); 10–19 days (OR = 17.57, p < 0.01); 20–29 days (OR = 15.69, p < 0.01) and used daily (OR = 18.79, p < 0.01) were at higher odds of using e-cigarettes compared to respondents who perceived the typical student was not a current smoker. Among respondents who perceived the typical student to be a current alcohol user, 1–2 days (OR = 2.05, p < 0.01); 3–5 days (OR = 2.73, p < 0.01); 6–9 days (OR = 2.19, p < 0.01); 10–19 days (OR = 2.42, p < 0.01); 20–29 days (OR = 3.38, p < 0.01) and used daily (OR = 3.27, p < 0.01) were at higher odds of using e-cigarettes compared to respondents who perceived the typical student was not a current alcohol user. Among respondents who perceived the typical student to be a current marijuana user, 1–2 days (OR = 2.48, p < 0.01); 3–5 days (OR = 3.18, p < 0.01); 6–9 days (OR = 3.86, p < 0.01); 10–19 days (OR = 4.02, p < 0.01); 20–29 days (OR = 4.75, p < 0.01) and used daily (OR = 3.59, p < 0.01) were at higher odds of using e-cigarettes compared to respondents who perceived the typical student was not a current marijuana user.</p> <hd id="AN0174908847-12">Discussion</hd> <p>Overall, a very small number of respondents in our sample (5%) were classified as current e-cigarette users. While the percentage of college students in this investigation reporting past month e-cigarette use may appear lower than other published estimates, there are several methodological considerations to note which may account for this. First, all respondents to the NCHA were included in this investigation. Other investigations citing higher e-cigarette use among 18–25 year old Americans (a) recruited persons who reported smoking at least one combustible cigarette in the past month,[<reflink idref="bib49" id="ref71">49</reflink>] (b) focused on single institution convenience samples,[<reflink idref="bib3" id="ref72">3</reflink>],[<reflink idref="bib25" id="ref73">25</reflink>] or (c) present data specific to high-school seniors.[<reflink idref="bib38" id="ref74">38</reflink>] Despite few students reporting personally vaping, more than seven out of every ten respondents thought the 'typical student' on their campus was an e-cigarette user. Exposure-response relationships among cigarettes, alcohol, and marijuana users were present, such that the likelihood of current vaping increased significantly as substance use increased. Similarly, as perceptions of typical student substance use increased, respondents were far more likely to contend the typical student used e-cigarettes.</p> <p>Findings herein highlight the important and profound impact perceptions of peer behavior have on individual behavior. Simply put, "social norms exert strong influences on individuals to conform to group behavioral patterns and expectations, essentially establishing what individuals believe to be the status quo."[<reflink idref="bib50" id="ref75">50</reflink>] For instance, with regards to alcohol use, drinking behaviors among college students tend to increase linearly with the behaviors of peers.[<reflink idref="bib51" id="ref76">51</reflink>] Moreover, persons with greater substance use are more likely to identify others who use substances as close personal ties and also mirror the substance use of these peers.[<reflink idref="bib52" id="ref77">52</reflink>] Given our findings that the likelihood of current vaping increased significantly as substance use increased, peer influence on any substance use behavior has the potential to indirectly influence subsequent vaping behaviors.</p> <p>Though current users were in the minority of the current sample, current users have unique characteristics worth noting. Specifically, current e-cigarette users have been found more likely to endorse e-cigarette products as "safe and healthy choices" and also consider themselves to be in good to very good health.[<reflink idref="bib53" id="ref78">53</reflink>] Based on evidence to date, it is clear that e-cigarettes have concrete, dangerous health implications for users.[[<reflink idref="bib54" id="ref79">54</reflink>], [<reflink idref="bib56" id="ref80">56</reflink>]] Linking vaping behaviors to both short- and long-term health implications for college students will be an important endeavor for health promotion practitioners and researchers.</p> <p>Similar to other investigations exploring e-cigarette use among college students,[<reflink idref="bib53" id="ref81">53</reflink>],[<reflink idref="bib57" id="ref82">57</reflink>] male students (OR = 2.28, p < 0.01) in the current sample, in particular, were at higher odds of vaping compared to females. Consequently, health promotion programming should recognize the uniqueness of the cohort of students who use e-cigarettes, and tailor their programming and messaging accordingly. Such tailoring may include messaging that is "male-centric" or distributed via avenues where the majority of recipients are likely to be male, such as campus fraternities, clubs or intermural sports unique to men, and male-focused student groups.</p> <hd id="AN0174908847-13">Limitations</hd> <p>There are some limitations that should be considered with the research findings. First, the NCHA survey is entirely voluntary and self-report. Second, member institutions self-select to administer the NCHA. As a result, NCHA data may not be generalizable for students across all U.S. colleges and universities. Hence, this is a national survey; however, it may not be considered 'nationally representative.'[<reflink idref="bib58" id="ref83">58</reflink>] Thirdly, a common issue with the addictive behaviors research and drug abuse surveys is that study participants do not inevitably aspire to disclose that they are presently using or have used e-cigarettes, alcohol, marijuana, or other substances in the past, primarily due to privacy or social security reasons. Thus, even though the survey is anonymous, it is possible response bias exists. Finally, the NCHA represents secondary data, administered directly by its parent organization, the ACHA. Like other secondary data sources, researchers do not have the ability to alter the design and methodology employed, questionnaires utilized, or variables assessed.</p> <hd id="AN0174908847-14">Conclusion</hd> <p>Given the clear disconnect between the number of actual e-cigarette users and the perception of e-cigarette use among other students, it is important for future health promotion efforts on college campus to address this (mis)perception and provide accurate, reality-based social norms data for their specific campus. Respondents who used tobacco were at much higher odds of also using e-cigarettes. To reduce the percentage of tobacco users on their respective campuses, universities should work to ensure e-cigarettes, vaporizers, and other electronic nicotine delivery systems are all included in smoke-free and tobacco-free campus policies. Adoption of comprehensive and system-wide smoke-free and tobacco-free campus policies, as well as elimination of inaccurate social norms are important concurrent steps that all U.S. colleges and universities can undertake. Given the increased likelihood of vaping among current substance users, adoption of evidence-based substance use education, prevention, and reduction efforts should also have a positive, indirect effect on vaping behaviors. This investigation provides important foundational data for the contextualization of e-cigarette use among American college students. We recommend future investigations replication this investigation to determine whether college students actual e-cigarette use, as well as the perceived use among peers, has changed since the NCHA began tracking this behavior.</p> <hd id="AN0174908847-15">Conflict of interest disclosure</hd> <p>The authors have no conflicts of interest to report. The authors confirm that the research presented in this article met the ethical guidelines, including adherence to the legal requirements, of the United States of America and received approval from the Institutional Review Board (IRB) Administration of Texas A&M University.</p> <hd id="AN0174908847-16">Funding</hd> <p>No funding was used to support this research and/or the preparation of the manuscript.</p> <ref id="AN0174908847-17"> <title> References </title> <blist> <bibl id="bib1" idref="ref1" type="bt">1</bibl> <bibtext> Littlefield AK, Gottlieb JC, Cohen LM, Trotter DRM. Electronic cigarette use among college students: links to gender, race/ethnicity, smoking, and heavy drinking. J Am Coll Health. 2015; 63 (8): 523 – 529. doi: 10.1080/07448481.2015.1043130.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref2" type="bt">2</bibl> <bibtext> Copeland AL, Peltier MR, Waldo K. Perceived risk and benefits of e-cigarette use among college students. 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  Label: Title
  Group: Ti
  Data: Actual and Perceived E-Cigarettes Behaviors among a National Sample of U.S. College Students
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  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Anas+Khurshid+Nabil%22">Anas Khurshid Nabil</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9748-2426">0000-0002-9748-2426</externalLink>)<br /><searchLink fieldCode="AR" term="%22Adam+E%2E+Barry%22">Adam E. Barry</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-6527-6866">0000-0001-6527-6866</externalLink>)<br /><searchLink fieldCode="AR" term="%22Hye-Chung+Kum%22">Hye-Chung Kum</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-6882-8053">0000-0002-6882-8053</externalLink>)<br /><searchLink fieldCode="AR" term="%22Robert+L%2E+Ohsfeldt%22">Robert L. Ohsfeldt</searchLink>
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  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Journal+of+American+College+Health%22"><i>Journal of American College Health</i></searchLink>. 2024 72(1):109-117.
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  Label: Availability
  Group: Avail
  Data: Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Label: Peer Reviewed
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  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 9
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Smoking%22">Smoking</searchLink><br /><searchLink fieldCode="DE" term="%22Health+Behavior%22">Health Behavior</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Drinking%22">Drinking</searchLink><br /><searchLink fieldCode="DE" term="%22Marijuana%22">Marijuana</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Attitudes%22">Student Attitudes</searchLink><br /><searchLink fieldCode="DE" term="%22Peer+Influence%22">Peer Influence</searchLink><br /><searchLink fieldCode="DE" term="%22Beliefs%22">Beliefs</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Characteristics%22">Student Characteristics</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1080/07448481.2021.2024209
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0744-8481<br />1940-3208
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objective: Electronic cigarette use represents an important college health concern. This investigation assessed demographic and behavioral correlates associated with actual and perceived e-cigarette use among a national sample of American college students. Methods: Respondents (n = 19,861) comprised college students from over 40 distinct American higher education institutions. Multivariable logistic regression assessed whether (1) alcohol, tobacco or marijuana use were associated with e-cigarette use; (2) perceived peer use of alcohol, tobacco or marijuana were associated with perceived e-cigarette use. Results: Approximately 5% of survey respondents self-reported using e-cigarettes within the past month. More than 7 out of every 10 respondents, however, thought the 'typical student' was an e-cigarette user. As perceptions of typical student substance use increased, respondents were far more likely to contend the typical student used e-cigarettes. Discussion: In addition to adopting smoke-free campus policies, university officials should disseminate accurate information regarding e-cigarette behaviors of students.
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  Data: 2024
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  Data: EJ1408423
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        Value: 10.1080/07448481.2021.2024209
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 9
        StartPage: 109
    Subjects:
      – SubjectFull: Smoking
        Type: general
      – SubjectFull: Health Behavior
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Drinking
        Type: general
      – SubjectFull: Marijuana
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      – SubjectFull: Correlation
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      – SubjectFull: Student Attitudes
        Type: general
      – SubjectFull: Peer Influence
        Type: general
      – SubjectFull: Beliefs
        Type: general
      – SubjectFull: Student Characteristics
        Type: general
    Titles:
      – TitleFull: Actual and Perceived E-Cigarettes Behaviors among a National Sample of U.S. College Students
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