Karen M. Emmons, PhD, Henry Wechsler, PhD, George Dowdall, PhD, and Melissa ..... Mills S, Marcus S. Smoking initiation in the. United States: a role for ...
Predictors of Smoking among US College Students Karen M. Emmons, PhD, Henry Wechsler, PhD, George Dowdall, PhD, and Melissa Abraham, BA
Introduction The overall smoking prevalence in the United States has been reduced considerably over the past 20 years; however, there have been only minimal reductions in smoking prevalence among adolescents and young adults.-7 Recent data from the National Health Interview Survey suggest that 18% of smokers born between 1960 and 1962 did not start to smoke until their young adult years.7 Among college students, the prevalence of use of cigarettes within the previous 30 days has been reported as 24.5%. Interestingly, 40% of all college students have used cigarettes at least once during the previous 12 months, suggesting that considerable experimentation with smoking occurs during the college years. Although smoking among adolescents and young adults is associated with socioeconomic status and educational achievement, determinants of smoking among college students are largely unknown. The health behaviors of young adults are important because this group is in a transition between adolescence and early adulthood, a time during which unhealthy behaviors developed during adolescence may be malleable or may be consolidated into lifetime pattems.811 Because of both the health and lifestyle risks facing college smokers, it is important to understand the characteristics associated with smoking in this population and the factors that might be used to influence students' smoking behavior. The purpose of this paper is to explore the predictors of smoking among a large, representative national sample of students enrolled in American 4-year colleges. Identification of the characteristics associated with smoking among this population may lead to more effective intervention efforts.
Methods The data used in this study were obtained from a representative national sample of 140 four-year colleges. A random sample of 25 627 undergraduate students received a study survey; 17 592 students responded, yielding an overall response rate of 69% (response rate range = 60% to 80%).
Details of the sampling procedure and the characteristics of the participating colleges have been described elsewhere.12-14 Comparison of the nonparticipating schools with the 140 schools included in the final sample revealed that the only statistically significant difference was in enrollment size. Proportionately fewer small colleges (fewer than 1000 students) participated in the study; however, these colleges were oversampled, and thus sufficient numbers were available for statistical analyses. The purpose of the parent project, the Harvard School of Public Health College Alcohol Study, was to examine binge drinking among college students. The study survey provided detailed information about drinking behavior, as well as information about smoking, illicit drug use, demographic characteristics, family characteristics, living arrangements, lifestyle choices, and academic performance. Smoking status was based on self-reported use of cigarettes within the preceding 30 days. This research examined the antecedents and correlates of smoking. The statistical analysis built on several previous studies of substance use among college students.13,15,16 In the first stage of analysis, variables were examined individually to assess how each raised the likelihood of smoking. Once the individual predictors of smoking were identified, those predictors with odds ratios (ORs) of approximately 1.5 or more were examined in multiple logistic regressions; SAS Proc Logistic (version 6.07) was used in conducting these analyses. Age, race, and gender were kept in the final model, following standard epidemiological practice. The intraclass cluster correlation for this analysis was estimated by means of the generalized
Karen M. Emmons, Henry Wechsler, and Melissa Abraham are with the Harvard School of Public Health, Boston, Mass. Karen M. Emmons is also with the Dana-Farber Cancer Institute, Boston. George Dowdall is with the Department of Sociology, St. Joseph's University, Philadelphia, Pa. Requests for reprints should be sent to Karen M. Emmons, PhD, Division of Community-Based Research, Dana-Farber Cancer Institute, 44 Binney St, Boston, MA 02115. This paper was accepted November 15, 1996.
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TABLE 1 -Demographic Characteristics of the Sample of College Students (n =17 592) Sample, Female Unmarried Race White Black Asian Other Hispanic origin Less than 24 years old Smoking status Smoker Former smoker Never smoker Smoking prevalence by college year Freshman Sophomore Junior Senior
TABLE 2-Logistic Regression Results for Individual Correlates of Smoking among College Students (n = 17 592) Odds Ratio (95% Confidence Interval) Total Male Students Female Students
%
58 89
Demographics Male 224 years of age
White 81 6 7 6 7 83
22.3 25.0 52.7 22.0 22.3 23.8 24.0
estimating equation approach.7-9 The coefficient's magnitude (.018) was negligible.
Not Hispanic Body mass index Parents' education Precollege binge drinking Lifestyle choice Nonparticipation in athletics Athletics not important Religion not important Parties important Leisure activities Productive activities Member of Greek organization Uve in coed dorm Happiness Dissatisfied with education Unhappy Risk behavior Marijuana use Binge drinking (college) Multiple sex partners
0.97 (0.08, 1.10) 1.92 (1.68,2.20) 1.17 (0.97,1.42) 1.08 (0.98,1.19) 1.39 (1.26,1.53) 3.67 (3.33, 4.06)
1.04 (0.90,1.19) 1.05 (0.91,1.21) 0.80 (0.65, 0.99) 1.02 (0.391,1.14) 1.26 (1.12,1.41) 2.93 (2.62, 3.29)
0.98 (0.91, 1.06) 1.00 (0.91, 1.09) 1.48 (1.34,1.63) 0.99 (0.86, 1.14) 1.06 (0.98,1.14) 1.33 (1.24,1.43) 3.30 (3.07, 3.56)
1.09 (0.97,1.22) 1.29 (1.15,1.46) 3.10 (2.64, 3.64) 2.33 (2.10, 2.58) 1.65 (1.49,1.83) 1.24 (1.12,1.36) 1.29 (1.14, 1.47) 1.42 (1.27, 1.59)
1.59 (1.41, 1.79) 1.64 (1.46, 1.84) 2.31 (1.91, 2.80) 1.95 (1.74, 2.18) 1.36 (1.21, 1.54) 1.42 (1.26, 1.60) 1.49 (1.29,1.72) 1.05 (0.92, 1.21)
1.30 (1.19, 1.40) 1.45 (1.33,1.57) 2.76 (2.44, 3.12) 2.12 (1.97, 2.29) 1.52 (1.41, 1.65) 1.31 (1.21, 1.41) 1.38 (1.25, 1.51) 1.25 (1.15, 1.36)
1.46 (1.23,1.72) 1.34 (1.16, 1.56)
1.62 (1.36, 1.92) 1.41 (1.19,1.68)
1.52 (1.35, 1.72) 1.37 (1.23, 1.54)
8.61 (7.52, 9.86) 5.22 (4.71, 5.79) 2.80 (2.25, 3.49)
5.44 (4.74, 6.23) 4.69 (4.13, 5.34) 1.65 (1.34, 2.02)
6.78 (6.17, 7.46) 4.89 (4.51, 5.29) 2.08 (1.79, 2.41)
Note. Referent categories, which are not presented, had odds ratios of 1.0 and were the negation of the variable presented (e.g., the referent category for gender was female).
Results Sample Description Demographic characteristics are presented in Table 1. In this sample, 22.3% of the full-time students at 4-year colleges had smoked during the previous 30 days, and 25% were classified as former smokers (16% abstinent for at least 12 months, 9% abstinent for 1 to 12 months). Among the smokers, 33.7% smoked half a pack per day or more; 14% smoked one pack per day or more. Smoking prevalence was not related to year in college. No gender differences in smoking prevalence were found. The independent variables were grouped into five logical categories to aid interpretation: (1) demographic variables, (2) precollege drinking behavior, (3) college lifestyle choices (e.g., attitudes toward and participation in various activities, including parties, religion, athletics, etc.), (4) high-risk behaviors (e.g., binge drinking, marijuana use, multiple sex partners), and (5) self-reported happiness and satisfaction with education. Table 2 presents results of individual logistic regression analyses in which the dependent variable was smoking status (whether or not a student had smoked
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in the previous 30 days) and the independent variable was an individual predictor.
Univariate Analyses
Demographic variables. Race (being White) was a moderate predictor of smoking status for women but not for men; no relationships were found between smoking status and Hispanic ethnicity for women, but there was a relationship for men. The educational level of students' parents (defined as at least one parent graduating from college), used as a crude measure of social class, was found to have a small relationship with smoking. Precollege drinking behaviors. The primary measure of precollege drinking behavior was participation in binge drinking during high school. This variable had a strong relationship with smoking status and was found to raise the likelihood of smoking in college more than threefold (OR = 3.30). College lifestyle choices. As a broad indicator of college lifestyle choices, students rated their participation in and attitudes toward several types of activities (e.g., community service, academics, religion, athletics, arts, leisure activities). Sev-
eral lifestyle choices predicted smoking status, including not participating in intercollegiate athletics (men only), considering athletics to be not very important, considering religion to be not very important, endorsement of parties as important or very important, and level of participation in leisure activities. An index of nonparticipation in productive activities was also related to smoking status. Being a member of a fratemity or sorority increased the likelihood of a student being a smoker, as did residing in a coed dorm (women only). High-risk behaviors. The co-occurrence of health-threatening behaviors was demonstrated by the large odds ratios for current marijuana use and binge drinking (6.78 and 4.89, respectively). Gender differences were noted, particularly in terms of marijuana use. In addition, having two or more sex partners in the previous month increased the likelihood of smoking among men and almost tripled the likelihood of smoking among women. Self-reported happiness. Overall unhappiness with life was related to smoking status. Dissatisfaction with one's education was found to be a moderate predictor of smoking status. American Joumal of Public Health 105
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Multivariate Analyses The final multivariate results showed small but interesting differences by gender (see Table 3). When the other variables were taken into account, gender emerged as a predictor of smoking, with men less likely to smoke than women. Race/ethnicity was not related to smoking status. The high-risk behavior variables were the strongest predictors of smoking status. Using marijuana and binge drinking during college both independently raised the likelihood of smoking substantially (ORs = 3.78 and 3.28, respectively). In addition, high school binge drinking moderately increased the likelihood of smoking in college, as did having multiple sex partners in college. Not participating in athletics was a predictor of smoking status. Participation in leisure activities and dissatisfaction with education were also predictors of smoking.
Discussion This representative national sample provided a unique opportunity to examine the predictors of smoking behavior among college students. Lifestyle characteristics clearly emerged as important predictors of smoking behavior. The results suggest that other high-risk behaviors, such as using marijuana, drinking heavily, and having multiple sex partners, are the strongest correlates of smoking status among this population. Other characteristics of a hedonistic lifestyle were also predictive, such as endorsement of parties as important and participation in leisure activities. These relationships were stronger for women. Engaging in binge drinking in high school increased the likelihood of smoking in college. This may indicate that smoking among college students is part of a risktaking lifestyle initiated well before college. Nonparticipation in athletics increased the likelihood of smoking. This is in contrast to previous findings suggesting that binge drinking is associated with active participation in athletics.'2 Such findings have important implications for health education and health promotion interventions among college populations, which often assume that a similar message must be delivered regardless of the substance being discussed. These results may be useful for consideration in the development of interventions designed to target smoking and other substance use behavior among college students. There are several intervention implications of these findings. First, students who were not involved in the productive 106 American Journal of Public Health
TABLE 3-Multivariate Logistic Regression Results for Prediction of Smoking Status among College Students (n = 17 592) Odds Ratio (95% Confidence Interval) Male Students Total
Female Students
Demographics Male L24 years of age White Parents' education Precollege binge drinking Lifestyle choice Nonparticipation in athletics Religion not important Leisure activities Productive activities Risk behavior Marijuana use Binge drinking (college) Multiple sex partners
1.44 (1.22,1.71) 1.14 (0.96, 1.34) 1.19 (1.06, 1.33) 1.91 (1.69, 2.16)
1.25 (1.05, 1.49) 0.63 (0.53, 0.76) 1.13 (0.99, 1.29) 1.66 (1.44, 1.91)
0.76 (0.69, 0.84) 1.35 (1.19,1.52) 0.89 (0.79, 1.01) 1.17 (1.07, 1.28) 1.78 (1.63, 1.95)
1.25 (1.09, 1.42) 1.71 (1.41, 2.07) 1.29 (1.14, 1.46) 1.32 (1.06,1.63)
1.91 (1.66, 2.19) 1.32 (1.05, 1.65) 1.09 (0.95, 1.26) 1.40 (1.14,1.73)
1.53 (1.39,1.68) 1.56 (1.34, 1.79) 1.19 (1.09, 1.31) 1.35 (1.17,1.58)
4.68 (3.99, 5.49) 3.13 (2.76, 3.55) 1.71 (1.29, 2.26)
3.05 (2.59, 3.58) 3.55 (3.03, 4.16) 1.09 (0.85,1.39)
3.78 (3.38, 4.23) 3.28 (2.98, 3.62) 1.32 (1.10, 1.59)
Note. Referent categories, which are not presented, had odds ratios of 1.0 and were the negation of the variable presented (e.g., the referent category for gender was female). Likelihood ratio chi-square statistics were 1670.96 (11 dt, P = .0001) for men and 1016.29 (11 dt, P = .0001) for women.
aspects of university life and who were dissatisfied with their educational experience were more likely to be smokers. Efforts to engage these students in academic or other types of college-based activities may be an important part of helping them to develop healthier lifestyles. Second, the likelihood of smoking was greatly increased among students who engaged in other high-risk behaviors. Intervention efforts need to take into account co-occurrence of smoking with use of alcohol and other substances, and the possibility that students may have developed dependencies on multiple substances. Third, the gender differences in these results are particularly interesting. Young women who adopt more risk-taking lifestyles are more likely to smoke. The college period offers a number of unique opportunities for intervention with this group. For example, residence halls and sororities may provide a strategic channel for development and modification of social norns around health behaviors. In addition, residence advisors and academic advisors often develop ongoing relationships with students and, with proper training, could provide interventions addressing these important health behaviors. Helping these at-risk students to develop more productive lifestyles may be an appropriate role for college personnel. These results suggest that college may present an important opportunity to intervene with smokers in regard to multiple
health risk factors. The development of effective interventions and substance abuse policies for colleges and universities is likely to help reduce the long-term morbidity and mortality related to smoking facing this large population of young smokers. D
Acknowledgments This research was supported by grants from The Robert Wood Johnson Foundation, Liberty Mutual, and the Boston Foundation. We gratefully acknowledge the biostatistical contributions of Dr Hang Lee.
References 1. Making Health Communication Programs Work: A Planner's Guide. Bethesda, Md: National Institutes of Health; 1989. NIH publication 89-1496. 2. The Health Consequences of Smoking: A Report of the Surgeon General. Washington, DC: US Dept of Health and Human Services; 1989. CDC report 89-8411. 3. Healthy People 2000: National Health Promotion and Disease Prevention. Washington, DC: Public Health Service; 1991. 4. Johnston LD, O'Malley PM, Bachman JG. National Survey Results on Drug Use from the Monitoring the Future Study, 1975-1993. Volume 2. College Students and Young Adults. Washington, DC: US Government Printing Office; 1994. NIH publication 94-3810. 5. Nelson DE, Giovino GA, Shopland DR, Mowery MS, Mills SL, Eriksen MP. Trends in cigarette smoking among US adolescents, 1974 through 1991. Am J Public Health.
1995;85:34-39.
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Public Health Briefs 6. Bachman JG, Wallace JM, O'Malley PM, Johnston LD, Kurth CL, Neighbors HW. Racial/ethnic differences in smoking, drinking, and illicit drug use among American high school seniors: 1976-1989. Am J Public Health. 1991;81:372-377. 7. Pierce JP, Naquin M, Gilpin E, Giovino G, Mills S, Marcus S. Smoking initiation in the United States: a role for worksite and college smoking bans. Public Health Rep. 1991;83: 1009-1013. 8. Schorling JB, Gutgesell M, Klas P, Smith D, Keller A. Tobacco, alcohol and other drug use among college students. J Subst Abuse. 1994;6:105-1 15. 9. Gray NL. The relationship of cigarette smoking and other substance use among college students. JDrug Educ. 1993;23:117-124. 10. Gray NL, Donatelle RL. A comparative analysis of factors influencing smoking
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11.
12.
13.
14.
behaviors of college students: 1963-1987. J Drug Educ. 1990;20:247-255. Martin CS, Clifford PR, Clapper RL. Patterns and predictors of simultaneous and concurrent use of alcohol, tobacco, marijuana, and hallucinogens in first-year college students. J Subst Abuse. 1992;4:319-326. Wechsler H, Davenport A, Dowdall G, Moeykens B, Castillo S. Health and behavioral consequences of binge drinking in college: a national survey of students at 140 campuses. JAMA. 1994;272:1672-1677. Wechsler H, Dowdall GW, Davenport A, Castillo S. Correlates of college student binge drinking. Am J Public Health. 1995;85: 921-926. Wechsler H, Dowdall GW, Davenport A, Rimm EB. A gender-specific measure of binge drinking among college students. Am J Public Health. 1995;85:982-985.
15. Andreasson S, Brandt L, Romelsjo A, Allebeck P. Antecedents and covariates of high alcohol consumption in young men. Alcohol Clin Exp Res. 1992;16:708-713. 16. Andreasson S, Allebeck P, Brandt L. Predictors of alcoholism in young Swedish men. Am JPublic Health. 1993;83:845-850. 17. Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics. 1988;44:1049-1060. 18. Castillo S. Analyzing Multilevel or Hierarchically Organized Survey Data Using Generalized Estimating Equations: An Assessment of the Risk ofAlcohol Abuse among College Students. Unpublished paper, Department of Biostatistics, Harvard School ofPublic Health, 1995. 19. Dowdall GW, Wechsler H. The high binge college: correlates and characteristics. Presented at the 123rd Annual Meeting of the American Public Health Association, October 1995, San Diego, Calif.
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