South African College Students' Attitudes Regarding Smoke-Free Policies in Public, on Campus, and in Private Spaces

S. K. Narula¹, C. J. Berg^1*, C. Escoffery¹and E. Blecher²

¹Behavioral Sciences and Health Education, Emory University School of Public Health, 1518 Clifton Rd NE, Atlanta, GA 30322, USA

²International Tobacco Control Research Program, American Cancer Society, 250 Williams St NW, Atlanta, GA 30303, USA

*Corresponding Author:

Carla J. Berg, PhD
Department of Behavioral Sciences and Health Education
Emory University School of Public Health, 1518 Clifton Road
NE, Room 524, Atlanta, GA 30322, USA
Tel: 404-727-7589
Fax: 404-727- 1369
E-mail: cjberg@emory.edu

Received October 20, 2011; Accepted December 20, 2011; Published December 24, 2011

Citation: Narula SK, Berg CJ, Escoffery C, Blecher E (2012) South African College Students’ Attitudes Regarding Smoke-Free Policies in Public, on Campus, and in Private Spaces. J Addict Res Ther S1:005. doi:10.4172/2155-6105.S1-005

Copyright: © 2012 Narula SK, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Abstract

Background: Despite the increase in smoke-free policies globally, there has been limited research regarding reactions to them among young adults. Thus, the objectives of the current study are to examine smoking behaviors and attitudes toward smoke-free policies among South African college students.

Design and Methods: In Summer 2010, University of Cape Town students were recruited for surveys and focus groups through fliers and classroom announcements. Survey assessments included sociodemographics, smoking behaviors, and attitudes toward smoke-free policies. The online survey was completed by 103 college students, and 4 focus groups among 27 college smokers were conducted.

Results: Of 103 survey participants, 41.7% (n=43) were current (past 30-day) smokers. Correlates of current smoking included being male (OR=0.32, p=.020), having more friends that smoke (OR=1.32, p=.031), more frequently consuming alcohol (OR=1.07, p=.060), and having used marijuana in the past 30 days (OR=3.75, p=.029). Participants reported high levels of approval of smoke-free policies in public (93.2%) and on campus (60.2%) and frequently implemented smoke-free policies in their homes (67.0%) and cars (73.8%). Correlates of receptivity to public policies included not living with smokers (p=.020) and being nonsmokers (p=.003). Receptivity to a smoke-free campus was associated with fewer friends who smoke (p=.022), having nonsmoking parents (p=.014), and being nonsmokers (p<.001). Correlates of having a smoke-free home included not using alcohol in the past 30 days (p=.053), having nonsmoking parents (p=.024), and not living with smokers (p<.001). Having a smoke-free car was associated with not recently using alcohol (p=.002), living on campus (p=.037), and being nonsmokers (p=.009). Focus group data indicated that, despite support for smoke-free policies, enforcement of public and campus policies is limited.

Conclusions: Future tobacco control efforts might focus cessation among young adults and enforcement of existing public and campus policies in South Africa.

Introduction

Smoking is the third leading cause of death in South Africa [1]. Eight percent of all deaths, or almost 50,000 South African deaths per year, are a direct result of smoking [1,2]. It is the number one cause of many cancers in South Africa [1,3].

Smoking in South Africa is prevalent. Over 22% of adults (2002- 2003) and 24% of youth (2008) smoke [4]. Approximately 16% of adults report smoking daily [4]. There is a large gender imbalance, with 35.3% of males and 10.5% of females smoking [5,6]. Although smoking prevalence among adults has decreased from 32.6% in 1993 to 23.7% in 2009 [3], among 20-24 year olds, prevalence has remained relatively unchanged, increasing slightly from 20.5% in 2001 to 21.7% in 2009 [5]. Along with the declines in smoking prevalence, between 1993 and 2009, aggregate consumption declined by 30.9% and per capita consumption by 49.3%. Van Walbeek [7] ascribes tax induced price increases of 162.8% between 1993 and 2009 as the reason for this decline. In order to reap the benefits of tobacco control policies, a major focus must be to reduce youth smoking, as they are the most vulnerable, high-risk demographic. Overall, young people are less addicted and capable of quitting more easily, highlighting the importance of intervening early [3].

In addition, exposure to second-hand tobacco smoke causes death, disease, and disability [8]. It kills up to 600,000 people every year [8]. About one third of adults are exposed to second-hand smoke on a regular basis globally. Second-hand tobacco smoke has similar components to inhaled or mainstream smoke. More importantly, it is three to four times more toxic per gram of particulate matter than mainstream tobacco smoke [8].

In 1993, South Africa established the Tobacco Products Control Act, which restricted smoking in public places, banned smoking on public transport, regulated the sale and advertising of tobacco products, and regulated packaging with warning labels [9]. In 2005, South Africa ratified the WHO Framework Convention on Tobacco Control (FCTC) [10]. As a result, there has been an increased interest in reducing tobacco use and secondhand smoke exposure.

The Behavioral Ecological Model (BEM) [11] highlights social ecological systems and the connection from the highest level of society (e.g., tobacco products control act and taxes on cigarettes) to individual factors (e.g., smoking attitudes, behaviors, and patterns). In the context of the current study, we examine individual factors and sociocultural and community factors related to the policies affecting the general societal and cultural norms around smoking and secondhand smoke exposure in South Africa. Specifically, we aimed to identify sociodemographic and psychosocial correlates of current smoking and examine reactions to public and campus smoking policies and implementation of private smoke-free policies among South African college students.

Design and Methods

This study used a mixed methods approach based on the Behavioral Ecological Model. Specifically, we used an online survey and focus group methodology in order to comprehensively evaluate South African college student smoking behaviors and attitudes toward smoke-free policies. This approach allows for a greater depth of information, which is appropriate given the fact that relatively little is known about these topics among this particular population. Our study was approved by the Emory University Institutional Review Board (IRB00044253) and the UCT Institutional Review Board (Reference: CF/SoE/EU/August/ 2010).

Survey research methods

Eligible students were at least 18 years of age and enrolled at least part-time as undergraduate or graduate students at UCT. The population was chosen based on the convenience of accessing students at UCT as well as its size and diversity in population. In 2010, information regarding this study was posted the survey on the school’s online portal, included in flyers, sent via email, delivered in person through announcements in lectures, etc.

Measures

The online survey contained 46 questions, lasting less than 10 minutes, assessing smoking behaviors, patterns, motives, and demographic characteristics.

Demographics: The demographic characteristics assessed included age, gender, ethnicity (white, African, coloured, Indian, other), and living situation (on campus, off campus).

Smoking status: Participants were asked, “In the past 30 days, on how many days did you smoke a cigarette (even a puff)?” and “On the days that you smoke, how many cigarettes do you smoke on average?” These questions have been validated and proven to be reliable based on previous studies [12-14]. Students who reported smoking at least one day in the past 30 days were considered current smokers [12,15].

Social influences on smoking: Participants were also asked “Out of your five closest friends, how many of them smoke cigarettes?” [16]; “Did at least one of your parents smoke?”; and “Do you live with anyone who smokes cigarettes?”

Attitudes regarding public smoke-free policies: Participants were asked, “How do you feel about the law prohibiting smoking in all public buildings?”; “How do you feel about the law prohibiting smoking in all workplaces?”; “How do you feel about the law prohibiting smoking in all restaurants?”; and “How do you feel about smoking being prohibited in bars?” using a four-point Likert-type scale with response options ranging from 0 = strongly disapprove to 3 = strongly approve.

Attitudes regarding campus smoking policies: Participants were asked, “How do you feel about the current smoking policies on campus?” and “How would you feel about a policy making this campus completely smoke-free?” using a four-point Likert-type scale with response options ranging from 0 = strongly disapprove to 3 = strongly approve.

Private smoking policies: Participants were asked which of the following best describes the rules about smoking in their homes: (a) no one is allowed to smoke anywhere; (b) smoking is allowed in some places or at some times; or (c) smoking is permitted anywhere; there are no rules [17]. A similar item was adapted to examine rules about smoking in cars.

Data analysis

First, descriptive statistics were conduct including frequencies and percentages for categorical variables and means and standard deviations for continuous variables. Second, bivariate analyses were conducted using Chi-squared, t-tests, and correlations as appropriate examining factors associated with current smoking status, reactions to public and campus smoke-free policies, and implementation of private restrictions. Each of these outcomes was then examined through multivariate regression modeling. Binary logistic regression was used for current smoking status, readiness to quit among smokers, recent quit attempts among smokers, and implementation of private smoking restrictions. Ordinary least squares regression was used to model factors associated with smoking level among smokers, attitudes toward smoking, and reactions to public and campus policies. Backwards stepwise entry was used to determine which variables were allowed to remain in the model. Significance was set at α = 0.05 for all tests. Survey data analyses were conducted in SPSS 18.0

Focus group research methods

Participants and recruitment: Eligibility criteria for the focus groups included being at least 18 years of age, being enrolled at least part-time as a student at UCT, and having smoked in the past 30 days. Students were informed about the focus groups through communication on the online student portal, flyers, word of mouth, and announcements in lectures. Students sent emails to the PI expressing their interest in the focus groups for certain dates.

Procedures: The research team completed 4 focus groups, with 3-13 participants (total N = 27), lasting one hour. Focus groups were conducted in centrally located classrooms at times convenient for students, particularly after peak course hours. Focus groups included current smokers, including both genders and various ethnicities. Prior to beginning the focus groups, participants read and signed an informed consent form and completed a brief questionnaire assessing sociodemographic characteristics (including age, gender, and ethnicity) and smoking behaviors. The focus group moderator’s guide assessed factors related to smoking (i.e., barriers, motivators, and quitting smoking); attitudes regarding smoke-free policies; and decisions to implement smoking restrictions in private spaces (i.e., in one’s home or car). All group sessions were audiotaped, transcribed verbatim, and observed by a research assistant who also took field notes. After each session, the moderator and research assistant debriefed.

Data analysis

Qualitative data were analyzed according to the principles outlined in Morgan & Krueger [18]. Transcripts were independently reviewed by the two members of the authorship team to generate preliminary codes. They then refined the definition of primary (i.e., major topics explored) and secondary codes (i.e., recurrent themes within these topics) and independently coded each transcript. The independently coded transcripts were compared, and consensus for coding was reached. Quantitative data from the focus group surveys were analyzed using SPSS 18.0.

Results

Survey research

Table 1 describes survey participant characteristics. Of 103 survey participants, 46.6% were female, 53.4% were white, and the average age was 21.36. Overall, 41.7% (N=43) smoked in the past 30 days (Table 1).

Table 1: Bivariate analyses examining differences between current smokers and nonsmokers among the survey participants.,/

Correlates of smoking status

In comparison to current smokers, nonsmokers were more receptive to all public policies (p<.001) and a complete campus-wide ban (p=.052; Table 1). Nonsmokers were also more likely to have complete car (p<.001) but not complete home bans (p=.164).

The multivariate model identified factors related to current smoking status. The factors included being male (OR=0.32, CI (0.12, 0.83), p=.020), having more friends who smoke (OR=1.32, CI (1.03, 1.70), p=.031), more frequently consuming alcohol in the past 30 days (OR=1.07, CI (1.00, 1.15), p=.060), and having used marijuana in the past 30 days (OR=3.75, CI (1.14, 12.31), p=.029).

Correlates of receptivity to smoke-free policies

Receptivity to a ban in all public places was less among current smokers (M=2.44, SD=.12, p<.001) than among nonsmokers (M=2.83, SD=.05, p<.001). The multivariate regression model indicated that significant correlates of receptivity to a ban in all public places included not living with a smoker (Coefficient= -0.28, CI (-0.52, -0.04), p=.020) and not having smoked in the past 30 days (Coefficient= -0.36, CI (-0.60, -0.13), p=.003; Table 2).

Correlates of receptivity to a smoke-free campus

Smokers (M=0.98, SD=1.10, p=.052) were less receptive to a smokefree campus than nonsmokers (M=2.35, SD=0.82, p= .052). The results of the multivariate model indicated that correlates of receptivity to a smoke-free campus including fewer friends who smoke (Coefficient= -0.08, CI (-0.16, -0.01), p=.022), not having parents who smoked (Coefficient= -0.45, CI (-0.80, -0.09), p=.014), and being a nonsmoker (Coefficient= -1.17, CI (-1.55, -0.80), p<.001; Table 2).

Correlates of smoke-free policies in the home and car

Smokers, compared to nonsmokers, were less likely to have a home smoking ban (N(%)=26 (60.5%), p=.233 vs. N(%)=43 (71.7%), p=.233) and car ban (N(%)=24 (55.8%), p<.001 vs. N(%)=52 (86.7%), p<.001). In the multivariate model predicting having a complete smoking ban in the home, correlates included not using alcohol in the past 30 days (OR=0.94, CI (0.87, 1.00), p=.053), not having parents who smoked (OR=0.33, CI (0.12, 0.86), p=.024), and not living with a smoker (OR=0.18, CI (0.06, 0.48), p<.001; Table 2). The multivariate model predicting having a smoke-free car indicated that significant correlates included not using alcohol in the past 30 days (OR=0.89, CI (0.83, 0.95), p=.002), living on campus (OR=0.21, CI (0.04, 0.91), p=.037), and being a nonsmoker (OR=0.24, CI (0.08, 0.70), p=.009; Table 2).

Focus group research

Of the 27 focus group participants, the average age was 20.37 and the majority of the students were male (63.0%) and African (59.3%). On average, participants smoked 20.48 (SD=11.18) days in the past 30 days, with average cigarette consumption of 6.15 (SD=5.44) on smoking days.

Reactions to smoke-free policies

Table 3 summarizes the themes that surfaced in the four focus group discussions. Participants expressed approval of public smokefree policies, although some expressed disapproval of smoking sections in restaurants and bars. Some students also reported that restrictions in restaurants and bars caused them to decrease the frequency of smoking and increased feelings of isolation. One theme that emerged was lack of enforcement of tobacco control policies, including a lack of fines for smoking in public places, no regulations selling to minors, and law enforcement being occupied with other significant issues such as crime (Table 3).

Table 2: Regression models predicting reactions to smoke-free policies in public, on campus, and in private spaces.

At UCT, campus policies included an indoor smoking ban in all university buildings, with smoking allowed anywhere outdoors. When asked about a potential 100% tobacco-free campus, most students reported that the ban would not influence their decision to attend the university. However, if the ban was put into place, some students reported that they would smoke elsewhere, smoke where they would not be caught, and spend less time on campus. Many students reported that there is significant lack of enforcement on campus, particularly in the residence halls. Although the campus rules state that the university buildings are smoke-free, most people smoke freely in dorms, and they reported smoking alongside the resident assistants and university security that also smoke.

Among a majority of the participants, smoking restrictions in the home and car were implemented and considered favorable. Students reported having home restrictions due to the smell that smoking causes. However, some participants had partial bans allowing smoking only in the kitchen or in their private rooms. Students supported and respected others’ private restrictions. Participants also discussed not smoking among children or minors when in enclosed areas.

Social influences for smoking initiation and as barriers to cessation

Peers and families had a major influence on the initiation and maintenance of smoking. Many participants began smoking with their friends or older siblings. Many students have different smoking patterns while living at home with their parents and living independently at school due to parents’ lack of awareness of the child’s smoking, parental disapproval of smoking or restrictions against smoking in the home, and the social influences present when on campus.

Triggers for smoking

Some major triggers for smoking among student smokers included stress, social influences, alcohol consumption, and boredom. Students experienced majority of stress due to school and smoked significant amounts while studying. Social influences, such as peers smoking, smoking shown on television, and smoking depicted as attractive, seemed to promote smoking. Most participants described a natural combination of smoking while drinking. Smoking was reported to more frequently occur when drinking, going to clubs/bars, and being with others that smoke.

Discussion

This study is the first to document the smoking rates and reactions to smoke-free policies among a sample of college students in Cape Town, South Africa. Smoking rates among this sample of South African college students was 41.5%, which is higher than that of the general South African population in 2009 (22.9%) [4] and among 20-24 year olds (21.7%) [4]. This may be due to the fact that UCT is a college that may draw students from higher socioeconomic status (SES), and higher SES is associated with greater likelihood of smoking in South Africa [6]. Similar to the differences in smoking prevalence in the general South African population (35.3% of males; 10.5% of females) [5,6], current findings indicated that 58.3% of males smoked versus 30.2% of females.

The correlates of smoking in this study included having friends that smoked, consuming alcohol, and marijuana use. The finding regarding having more friends that smoked has also been shown in previous research that illustrates the influence of friends and parents on smoking initiation among youth [19]. In addition, previous studies have shown that high-risk behaviors including marijuana use and binge drinking are the strongest correlates of smoking status among college students [20,21]. Many focus group participants reported first trying smoking while consuming alcohol and commonly reported using marijuana, alcohol, and cigarettes concurrently. They also reported social influences as critical factors impacting smoking initiation, and both impeding and supporting cessation efforts.

In regard to smoke-free policies, smokers were less supportive of public, campus, and private smoke-free policies versus nonsmokers. Other factors associated with being less receptive to smoke-free policies included living with a smoker, having parents who smoked, and having more friends who smoke. Moreover, not implementing private restrictions was associated with greater alcohol consumption, having parents who smoked, living with a smoker, and living off campus. These findings highlight the social and environmental factors that influence attitudes about smoking and smoke-free policies and implementation of smoking restrictions in private spaces. This supports previous research indicating that parental smoking behaviors, peer influences, and living with smokers reduces one’s likelihood of having favorable attitudes toward smokefree policies or implementing them in personal spaces [22,23]. Participants reported insufficient enforcement of current campus and public smoke-free policies, such as a lack of fines for smoking in public places, law enforcement’s preoccupation with other issues, and law enforcement officials being smokers themselves. Research to promote compliance with policies has documented successful strategies including the installation of permanent ground markings that define smoke-free areas; moving benches and cigarette receptacles; recruiting volunteers to hand out reinforcement cards that include periodic rewards for compliance among smokers; and hosting educational and interactive events to publicize the policies [24]. Such strategies might bolster the effects of current policies.

Table 3: Reactions to smoking policies in public, on campus, and in private spaces and other smoking-related factors among college student smokers in South Africa.

This study has implications for future tobacco control research and practice. Efforts should focus on the environmental and social influences that promote smoking initiation and maintenance among South African youth and impact their attitudes toward smoke-free policies. Future research should further investigate the attitudes of students towards smoke-free policies in order to increase compliance with and receptivity to public and campus restrictions, as well as implementation of private restrictions among this population. Moreover, measures should be taken to promote enforcement of smoke-free policies.

Limitations

Limitations include the low survey response, use of a small convenience sample of college students at UCT, the limited generalizability, and the cross-sectional nature of this study. Also, although we used a mixed methods approach, we cannot be certain that we assessed all factors associated with smoking initiation, other smoking-related behaviors, or attitudes toward smoke-free policies. Despite these limitations, the fact that little research has examined smoking behaviors and reactions to smoke-free policies in South African youth, this is a critical study that might promote future research in this area.

Conclusions

Present findings indicate that smoking is associated with being male, social factors, and other substance use. College students were largely supportive of smoke-free policies in public and on campus, and the majority had implemented private smoke-free policies. Nonsmokers versus smokers were more receptive to public and campus policies and more likely to implement home restrictions. Unfortunately, enforcement of campus and public policies was a commonly reported challenge for policies being effective in reducing secondhand smoke exposure. Future tobacco control efforts should further examine social and environmental factors related to smoking initiation and attitudes about smoke-free policies among South African youth and explore intervention strategies for altering these factors.

Acknowledgements

This study was funded in part by the Emory University Rollins School of Public Health Global Field Experience fund. We would like to thank our collaborators at the University of Cape Town for their support in conducting this research.

References

1. Burki T (2008) Smoking in South Africa. Lancet Oncol 9: 1127.
2. Henderson A (2009) Law catches up with smokers. Cancer Association of South Africa.
3. Groenewald P, Vos T, Norman R, Laubscher R, van Walbeek C, et al. (2007) Estimating the burden of disease attributable to smoking in South Africa in 2000. S Afr Med J 97: 674-681.
4. World Health Organization. Implementing smoke-free environments. WHO Report on the Global Tobacco Epidemic, 2009.
5. South African Advertising Research Foundation. All Media and Product Survey (AMPS), 2009.
6. World Health Organization. Implementing smoke-free environments. WHO Report on the Global Tobacco Epidemic, 2009.
7. South African Advertising Research Foundation. All Media and Product Survey (AMPS), 2009.
8. Van Walbeek C (2005) The Economics of Tobacco Control in South Africa. Unpublished Dissertation, University of Capetown, Cape Town, SA.
9. National Council Against Smoking (Producer). New Tobacco Acts Become Law, 2009.
10. Townsend L, Flisher AJ, Gilreath T, King G (2006) A systematic literature review of tobacco use among adults 15 years and older in sub-Saharan Africa. Drug Alcohol Depend 84: 14-27.
11. Van Walbeek C (2005) The Economics of Tobacco Control in South Africa. Paper presented at the PhD Dissertation, University of Cape Town, SA.
12. Framework Convention Alliance (Producer). Updated Status of the WHO FCTC. Ratification and Accession by Country. WHO Framework Convention on Tobacco Control (FCTC), 2009.
13. Hovell M, Hughes SC (2009) The Behavioral Ecology of Secondhand Smoke Exposure: A Pathway to Complete Tobacco Control. Nicotine Tob Res11: 1254-1264.
14. (2008) American College Health Association-National College Health Assessment Spring 2007 Reference Group Data Report (Abridged). J Am Coll Health 56: 469-479.
15. Office of Applied Studies (Producer). The NSDUH Report, 2006.
16. (1997) Youth risk behavior surveillance: National College Health Risk Behavior Survey-United States, 1995. MMWR CDC Surveill Summ 46: 1-56.
17. Starr G, Rogers T, Schooley M, Porter S, Wiesen E, et al. (2005) Key Outcome Indicators for Evaluating Comprehensive Tobacco Control Programs. Atlanta, GA: Centers for Disease Control and Prevention.
18. Maibach EW, Maxfield A, Ladin K, Slater M (1996) Translating health psychology into effective health communication. J Health Psychol 1: 261-277.
19. Okah FA, Okuyemi KS, McCarter KS, Harris KJ, Catley D, et al. (2003) Predicting adoption of home smoking restriction by inner-city black smokers. Arch Pediatr Adolesc Med157: 1202-1205.
20. Morgan DL, Krueger RA (1998) The Focus Group Kit. Thousand Oaks, CA.
21. Chassin L, Presson CC, Sherman SJ, Montello D, McGrew J (1986) Changes in peer and parent influence during adolescence: Longitudinal versus cross-sectional perspectives on smoking initiation. Developmental Psychology 22: 327-334.
22. Emmons KM, Wechsler H, Dowdall G, Abraham M (1998) Predictors of Smoking among US College Students. Am J Public Health 88: 104-107.
23. Reed MB, Wang R, Shillington AM, Clapp JD, Lange JE (2007) The relationship between alcohol use and cigarette smoking in a sample of undergraduate college students. Addict Behav 32: 449-464.
24. Berg CJ, Lessard L, Parelkar PP, Thrasher J, Kegler MC, et al. (2011) College student reactions to smoking bans in public, on campus and at home. Health Educ Res 26: 106-118.

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