Journal of Adolescent Health 53 (2013) 363e367

www.jahonline.org

Original article

Longitudinal Predictors of Stopping Smoking in Young Adulthood

Elizabeth G. Klein, Ph.D., M.P.H. a,*, Jean L. Forster, Ph.D., M.P.H. b, and Darin J. Erickson, Ph.D. baDivision of Health Behavior and Health Promotion, Ohio State University College of Public Health, Columbus, OhiobDivision of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota

Article history: Received September 5, 2012; Accepted April 18, 2013Keywords: Young adult; Smoking cessation; Longitudinal survey

A B S T R A C TIMPLICATIONS AND

Purpose: This study aims to describe the longitudinal individual and environmental predictors ofstopping smoking among a group of young adult smokers.Methods: From a longitudinal population-based cohort of Midwestern youth, we analyzed semi-annual surveys when study participants were between the ages of 18 and 21 years. Using datafrom 2001e2008, we restricted analyses to individuals who, at age 18 years, reported smokingbetween 1 and 30 days in the previous month (n ¼ 1,022). We used generalized linear mixedmodeling to analyze demographic, attitudinal, and social-environmental predictors of stoppingsmoking over time.Results: After adjusting for smoking frequency at baseline, demographic and attitudinal factorsthat were associated with stopping smoking over time included increased age and attendingcollege; male gender, smoking frequency and agreeing that cigarettes are calming were signifi-cantly associated with continued smoking. Social-environmental factors associated with stoppingsmoking over time included a household ban on smoking and living in a state with a clean indoorair policy; factors associated with continued smoking included living with a smoker and havingclose friends who smoke.Conclusions: Both individual and social-environmental factors can serve as risk and protectivefactors for stopping smoking between ages 18 and 21 years. These factors should be used to refinemore effective smoking cessation and prevention interventions in young adults.

� 2013 Society for Adolescent Health and Medicine. All rights reserved.

* Address correspondence to: Elizabeth G. Klein, Ph.D., M.P.H., Division ofHealth Behavior and Health Promotion, Ohio State University College of PublicHealth, Columbus, OH 43210.

E-mail address: klein.232@osu.edu (E.G. Klein).

1054-139X/$ e see front matter � 2013 Society for Adolescent Health and Medicine. All rights reserved.http://dx.doi.org/10.1016/j.jadohealth.2013.04.012

CONTRIBUTION

Results fromthispopulation-based, longitudinal studyenhance our understandingof the role of individual andsocial-environmental factorsthatmaypromoteorserveasa barrier to smoking behav-iors. These results can beused to refine smokingcessation interventions tar-geting this challenging pop-ulation group.

Early adulthood is a time in life when individuals are highlysusceptible to social influences on behaviors, including smoking.Although nearly 90% of adult smokers try smoking by age18 years [1], young adults represent the highest-risk group forpast month smoking, with a reported 36% of 18- to 25-year-oldsreporting past month cigarette smoking [2]. Motivating thishigh-risk group to quit smoking is essential for both current andfuture health, because millions of American young people willeventually suffer premature mortality and/or reduced quality oflife as a result of smoking-related diseases.

Although quitting smoking by age 30 eliminates most of theexcess mortality [3,4], smoking cessation interventions amongyouth and young adults have not been highly successful [5,6]. Ina recent review of smoking cessation interventions among youngadults (aged 18e24 years), only two of 13 interventions reviewedshowed any effects beyond 6 months [6]. In the recent meta-analysis on cessation rates for young adults, Suls et al [7] foundthat any type of cessation intervention remains more effectivethan the success rates among non-participants. Factors witha robust association with quitting included not having friendswho smoke, not having intentions to smoke in the future,resisting peer pressure, older age of initiation, and havingnegative beliefs about smoking [5]. It was noted that in theliterature, longitudinal predictors of cessation in this age groupare “not well developed” [5]. As a result, population-based data

E.G. Klein et al. / Journal of Adolescent Health 53 (2013) 363e367364

on young adult smokers would add valuable information for thedevelopment of age groupespecific cessation strategies that maybe more effective in this challenging population group.

Slightly fewer than half (48%) of 18- to 24-year-old adults areenrolled in college [8]. Yet, most studies have focused on college-based studies of young adults, and few studies were conductedwith population-based samples. Given that the smoking preva-lence among young adults differs substantially between thosewho attend college or community college, or do not attendcollege [9,10], population-based samples of young adults will bean important advancement to the current literature, andrecommendations have been made to conduct future studies in“diverse young adult populations” outside formal college ormilitary settings [6].

Attitudes and perceptions of the benefits and disadvantagesof smoking are important predictors of smoking behaviorswithin this age group. The higher functional meaning of tobaccouse has been associated with increased smoking over time [11].Many adolescents and young adults perceive smoking as ameansfor weight control [12,13], particularly for female smokers [14].Concern over potential weight gain after cessation has beendemonstrated as a barrier to cessation attempts [15,16], and mayundermine cessation success [17].

In the present study, we focused on describing the predictors ofstopping smoking over time among a population-based cohort ofyoung adult smokers. Using data from semi-annual phone surveysregarding smoking behaviors, we evaluated several factors forassociation with stopping smoking over time between the ages of18 and 21 years. We hypothesized that there would be individualand social-environmental factors that significantly differentiatestopping smoking over time among young adults.We investigatedfactors at the individual and social-environmental levels asbarriers and facilitators to stopping smoking based on theseeffects in adolescent and adult populations.

Methods

Minnesota Adolescent Community Cohort study design

This study includes data from the Minnesota AdolescentCommunity Cohort (MACC) study. The MACC study is a pop-ulation-based cohort study that began in 2000, when 3,636participants between 12 and 16 years of age were recruited fromMinnesota, as well as 605 from four other upper Midwest states(North Dakota, South Dakota, Kansas, and Michigan). An addi-tional cohort of 12-year-old participants (n ¼ 584) was recruitedin 2001, for a total sample of 4,825 participants.

Before participant recruitment in Minnesota, the state wasdivided into 129 areas thought to reflect the local tobacco controlenvironment, fromwhich 60 were randomly selected; areas fromthe comparison states were purposefully selected based onurbanicity and demographic characteristics of the population.Wethen used a combination of probability and quota samplingmethods (to ensure equal age distribution) to recruit participantsfrom Minnesota and comparison states. Clearwater Research, Inc(Boise, ID) conducted recruitment by telephone by usingmodifiedrandom digit dial sampling. Households were called to identifythose with at least one teenager between the ages of 12 and 16years; within eligible households, respondents were selected atrandom from among age quota cells that were still open(response rate: 58.5% of known eligible participants). Additionaldetails regarding the study design are published elsewhere [18].

Participants completed a telephone survey every 6 monthsthat included questions about smoking-related attitudes andbehaviors. The interviews lasted 10e20 minutes, depending onthe smoking status of the participant. Participants received $15for completion of each survey. The interview was structured sothat spoken responses would not be revealing to anyone over-hearing the participant. The University of Minnesota InstitutionalReview Board approved this study and individual participants(and parents until participants were age 18 years) actively con-sented to participate.

The present study includes seven rounds of data collectedfrom all eligible participants when participants were between 18and 21 years of age; this equates to roughly 4 years of longitu-dinal data collected, starting in 2003. The MACC study partici-pants who completed three or more interviews between the agesof 18 and 21 years, and reported smoking at least once in theprevious month at age 18 years, were included in the presentstudy. Although the MACC study began in 2000, reference to the“baseline” throughout this article refers to the first round whenparticipants met age and smoking study inclusion criteria.

Measures

Outcome variable. For the present study, the outcome of interesthas been defined as “stopping smoking.” We consciously chosethis label because the stability of stopping smoking may not bepermanent; therefore, we chose not to use the descriptor ofsmoking cessation. As described above, 100% of the sample forthis study reported past month smoking at the baseline round.After baseline, we assessed current smoking at each round withthe item, “Now, thinking about the last 30 days, on how many ofthose days did you smoke a cigarette, even one or two puffs?” Atall rounds after baseline, stopping smoking was defined as thosewho reported 0 days of past month smoking, and continuedsmoking was defined as those who reported 1e30 days of pastmonth smoking.

Predictor variables. We selected predictor variables from demo-graphic, attitudinal, and social-environmental factors that havebeen associated with smoking behavior within this age group. Allpredictor variables were treated as time-varying variables whichwere reported on for every round, except for demographicvariables and age of initiation. Self-reported demographic vari-ables measured at the baseline included age (in years), sex, race/ethnicity (white/other), and age of initiation (in years)ddefinedas age at first whole cigarette.

There were several attitudinal variables related to tobaccoaddiction, confidence in quitting, and the functional meanings ofcigarette smoking. To assess self-reported addiction, participantswere asked, “On a scale from 1 to 5, where 1 is ‘not addicted at all’and 5 is ‘very addicted,’ how addicted are you to cigarettes?” Wedichotomized possible answers into “Somewhat/very addicted”(response of 4 or 5) or otherwise (response of 1e3). To assessself-reported confidence in quitting, participants were asked,“On a scale from 1 to 5, where 1 is ‘not at all sure’ and 5 is ‘verysure,’ how sure are you that you can quit smoking totally and forgood if you wanted to?” We dichotomized answers into “Some-what/very sure” (response of 4 or 5) or otherwise (response of1e3). Three attitudinal variables pertained to the functionalmeaning of tobacco: “When a person is feeling down, a cigarettecan really make them feel better,” “Cigarettes can help peoplecontrol their weight,” and “When someone’s angry or nervous,

Table 1Descriptive characteristics of adolescent smokers at age 18 years: MinnesotaAdolescent Community Cohort study

Variable Total (n ¼ 1,022)

Mean completed surveys, n 3.8 (range, 3e7)State of residenceMinnesota 84.9% (868)Kansas 7.7% (79)North Dakota 1.7% (17)South Dakota 1.3% (13)Michigan 1.2% (12)Other 3.2% (33)

Male 48.6% (497)White race 87.8% (897)Mean age (standard deviation) 18.3 (.22)Mean age of smoking first cigarette, years (standard

deviation)13.8 (2.3)

Smoking frequency at baselinePast-month smoker 19.8% (202)Past-week smoker 26.2% (268)Daily or near-daily smoker 54.0% (552)

Mean cigarettes/day at baseline (standard deviation) 7.7 (6.9)Stopped smoking at least once during follow-up 36.2% (270)Any family member smokes 50.9% (436)Mom smokes 31.5% (245)Dad smokes 31.3% (212)

Any close friend smokes 92.2% (942)College status at age 19 yearsNot in college 39.9% (326)2-year college 45.3% (370)4-year college 14.8% (121)

Living in at area with a local clean indoor air policy .5% (5)

Table 2Bivariate andmultilevel predictors of stopping smoking between 18 and 21 years:Results from Minnesota Adolescent Community Cohort study

Predictors Bivariate oddsratio (Confidence

interval)

Multivariateadjusted odds ratio(Confidence interval)

DemographicWhite race 1.00 (.78e1.27)Age, years 1.74 (1.62e1.86) 1.84 (1.70e2.00)Male gender .65 (.56e.76) .64 (.54e.76)Age of initiation, years 1.18 (1.14e1.23) 1.03 (.99e1.07)Attending any college 1.42 (1.28e1.57) 1.29 (1.08e1.54)Smoking frequency at baseline .40 (.37e.44) .47 (.42e.52)Number of cigarettes

smoked/day.70 (.13e3.64)

AttitudinalSelf-efficacy in quitting

smoking2.97 (.62e14.30)

Agreeing that cigarettes arecalming

.50 (.43e.58) .57 (.47e.68)

Agreeing that cigarettes aregood when you are down

.57 (.46e.70) .86 (.68e1.09)

Agreeing that cigarettes helpcontrol weight

.85 (.72e1.01)

Social-environmentalAnyone in household smokes .44 (.34e.51) .76 (.64e.92)Ban on smoking in home 2.40 (2.02e2.86) 1.65 (1.35e2.02)Having any close friends smoke .20 (.17e.25) .32 (.25e.40)Living in area with statewide

clean indoor air policy forbars and restaurants

1.82 (1.39e2.38) 1.44 (1.06e1.94)

Bolded values indicate p < .05.

E.G. Klein et al. / Journal of Adolescent Health 53 (2013) 363e367 365

a cigarette can calm them down.” Each item included responsecategories in a 5-point Likert-type scale ranging from stronglyagree (1) to strongly disagree (5). Higher scores on each variablerepresent greater perceived utility of tobacco use. Each func-tional meaning was dichotomized into “Somewhat/stronglyagree” (response of 3e5) or otherwise (response of 1 or 2).

Five variables measured potential influences on smokingbehavior from the immediate and distal social environment.Education level was self-reported as attending any type ofcollege during the study period, dichotomized as any collegeattendance or no college attendance. The number of four closestfriends who smoke cigarettes was dichotomized as having noclose friends smoke, or one or more friends smoke. Familysmoking was measured from several survey questions onwhether the participant’s mother, father, and/or siblings smokecigarettes (dichotomized as having at least one family membersmokes, or no family members smoke). Household smoking banwas measured by two survey items about whether residentsand guests are prohibited from smoking inside the participant’shome (defined as all residents/guests prohibited from smokinginside home, or residents and/or guests allowed to smoke inhome). Living in an area with a current smoking ban wasdetermined by whether the state of residence had a cleanindoor air policy that included a ban on workplace smoking,coded for each round; state of residence was self-reported bythe participant at every round, and the clean indoor air policystatus was coded for every round based on reports from a publicdatabase referencing the date and location of state clean indoorair policies [19].

Data analysis

Descriptive statistics on the study sample were means andpercentages, taken at the baseline round (age 18 years). Weassessed bivariate statistical associations for each of the predic-tors and the outcome variable of stopping smoking usinggeneralized logistic regression across seven rounds of data. Allvariables that achieved statistical significance (p < .05) in thebivariate regression analyses were included in the multilevellogistic regressionmodel, which assumed a binomial distributionand a logit link function. Results are reported as adjusted oddsratios (ORs) with the corresponding 95% confidence intervals(CIs); all analyses were conducted in SAS, version 9.2 (SASInstitute, Cary, NC).

Results

Table 1 shows baseline characteristics of the cohort partici-pants. Slightly less than of the study sample were male (48.6%);participants were predominantly white race (88%). More thanhalf (54%) were defined as regular smokers who smoked daily ornear daily, 26% smoked at least weekly, and 20% smoked a fewtimes in the past month; the mean number of cigarettes smokedper day was 7.7. The mean age of smoking initiation was 13.8years. Half had a family member who smoked cigarettes, andnearly all had one close friend who smoked (92%). Less than onethird of the study sample was in college at age 18 years.

Table 2 includes the predictors of stopping smoking over time,organized intodemographic, attitudinal, and social-environmentalpredictors. Bivariate and multivariate adjusted odds ratios arepresented, with multivariate results simultaneously modeling allpredictors significant in the bivariate model, as well as controlling

for the frequency of smoking at baseline. For every yearincrease in age, there was a 1.85 increase in odds of stoppingsmoking (p < .05). Men had significantly 37% lower odds ofstopping smoking over time than women (OR, .63; CI,

E.G. Klein et al. / Journal of Adolescent Health 53 (2013) 363e367366

.53e.75). Attending college was associated with an increasedodds of stopping smoking (OR, 1.17; CI, 1.03e1.33). For theattitudinal factors, only agreeing that cigarettes are calmingwas significantly associated with the outcome, with a 43%decreased odds of stopping smoking.

In the social environment, four factors were significantlyassociated with stopping smoking in the multivariate model.Having a household member who smokes was associated witha 25% decreased odds of stopping smoking over time, and havingany close friend smoking decreased odds of stopping smoking by69%. In contrast, smoking bans were associated with increases instopping smoking. Having a ban on smoking in the home wasassociated with a 66% increase in the odds of stopping smokingover time, and living in an area with a statewide ban on smokingin workplaces was associated with a 44% increase in the odds ofstopping smoking (p < .05 for both).

Discussion

In the present study, several significant predictors at theindividual level were associated with stopping smoking duringyoung adulthood. From the cessation literature, it is known thatindividual characteristics remain an important predictor ofattempting to quit andmaintaining cessation among young adultsmokers [20]. Consistent with other studies, age was positivelyassociated with stopping smoking [21], although in the presentstudy, age of initiation was not significantly associated withstopping smoking after adjusting for all other factors in ourmodel. Being female was associated with stopping smoking, butfew other studies have found a significant gender differencewithin this age group [22]; this finding warrants further explo-ration in other samples of young adults. Consistent with otherstudies on adolescents and young adults, having a more favor-able attitude about the function of smoking was associated withcontinued smoking [23].

Although college is an environment where social smokingand tobacco experimentation is common [9,24], a collegeeducation is generally considered as a protective factor forsmoking among young adults. In the present study, attendanceat any college was a predictor of stopping smoking [9].A promising development for tobacco-free social norms withinAmerican colleges is the diffusion of tobacco-free campuspolicies with over 700 tobacco-free campus policies [25]; thesepolicies will be an important element of a comprehensivestrategy for tobacco control within the high-risk environmentof college campuses. Support for environmental barriers tosmoking on college campuses, including tobacco-free campuspolicies as recommended by the American College HealthAssociation [26], has the potential to create an environmentalbarrier to smoking behaviors, which may affect social norms aswell as smoking behaviors.

The target population of young adults is uniquely susceptibleto both social and environmental influences to use tobacco [1],which makes the homes, workplaces, and social environmentswhere young adults spend time important venues for publichealth interventions to decrease smoking uptake and supportcessation [27]. Consistent with other studies, our results indicatethat individuals who have successfully quit smoking are morelikely to have a ban on smoking in the home, compared withthose without such rules [28]. The role of parental smoking hasbeen demonstrated to be a significant predictor of smokingbehavior, and hindrance to smoking cessation, even into young

adulthood [29]. As such, parental influences, householdmembers, and close friends all have significant influence onthose social and environmental triggers to smoking behavior.Living in an area with a statewide smoking ban for bars andrestaurants has been associated with reduced initiation inadolescents [30]. These policies may not only communicate thesocial norms around smoking acceptability [31]; they may createadditional workplace barriers, because young adults make upmore than one third of employees within hospitality settings[32].

Effective cessation strategies for adult populations may beless effective in this population, because young adults may beless likely to self-identify as smokers [33]. In a qualitative studyof attitudes toward smoking cessation methods, young adultsexpressed interest in interventions that focused on personal andsocial identities related to smoking, and were not explicitlyfocused on smoking cessation [34]. Ling et al [27,35] illustratedthat tobacco industry denormalization has been an effectivemeans to protect against smoking uptake and increase quitintentions within this age group. Future research is needed toexpand the evidence based on the strategies that are mosteffective with this challenging target population; as Cengalli et al[5] noted, interventions will “remain less than optimally effec-tive” until this evidence base is developed.

The present study has limitations. The MACC study samplerepresents the racial and ethnic makeup of the upper midwest-ern United States, but may not be generalizable to other regionswith greater heterogeneity. The use of past-month smoking asa proxy for cessation behaviors does not account for self-reportcessation attempts or actions; yet, it can be assumed that stop-ping smoking is a volitional behavior. Although self-reportedsmoking status has been demonstrated to have a high degreeof validity [36e38], smoking behavior was not validated bybiochemical tests; therefore, we cannot exclude some amount ofover-reporting of stopping smoking owing to its social accept-ability. Although smoking frequency was adjusted for at baseline,the present study does not assess nicotine dependence; whereasthe lack of information on explicit measures of dependenceremains a limitation, there is evidence that dependence isparticularly important for daily smokers, but not as stronglyassociated with quitting among non-daily smokers [39]. Furtherinvestigation into non-daily smoking patterns and stoppingsmoking is warranted. The definition of young adults for thepresent study was restricted to 18e21 years of age, which mayrepresent only a subset of young adulthood.

Our results focus on a behavioral definition of stoppingsmoking over a 4-year period among a group of regular smokersat age 18 years, and include several years of follow-up during thecritical period of ages 18e21 years. This prospective, multilevelinvestigation into predictors of stopping smoking providesfrequent measures of smoking behavior, which is especiallyimportant during this period of time when smoking behaviorsmay be in transition [40]. Results from the present studycontribute to our knowledge of the factors that predict stoppingsmoking among young adults, and may help inform efforts toidentify successful strategies for permanent cessation for thispriority population.

Acknowledgments

This research was funded by the National Cancer Institute(Grant R01 CA86191; Jean Forster, Principal Investigator) and

E.G. Klein et al. / Journal of Adolescent Health 53 (2013) 363e367 367

ClearWay Minnesota (Grant RC-2007-0018; Jean Forster andDebra Bernat, Co-Principal Investigators).

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