Research Papers Multiple Correlates of Cigarette Use Among High School Students Robert J. McDermott, Paul D. Sarvela, Pamela N. Hoalt, Srijana M. Bajracharya, Phillip J. Marty, Eileen M. Emery
ABSTRACT: A cross-sectional survey research design measured factors related to cigarette use among 2,212 senior high school students. Results showed 14.3% of the sample smoked cigarettes at leost occasionally, with 5.3% reporting they were doily smokers. About 12.8% indicated they were ex-smokers. Males ond females smoked at almost equal rates. and the percentage of 10th grade student smokers was slightly higher (16.4%) than the percentage of juniors and seniors who smoked. Approximately 22% of Hispanic students, 15% of Caucasian students, and 4.5% of African-American students reported smoking cigorettes at least occasionally. An initial regression analysis used 21 variables to predict cigorette smoking. A more parsimonious regression model (R’ = .28), using varioblesfrom the initial regression onalysis with significance levels of .01 or less, indicated the most important predictors of cigorelte use were ethnic group, ottitude toward femoles who smoke, close friends’ use of cigarettes, personal use of marguano, best friend’s use of cigarettes, personal use of alcohol, and school selfesteem. Implications for school health programs ore addressed. ( J Sch Health. 1992;62(4): 146-150)
R
esearch confirms smoking as the most important preventable cause of morbidity and mortality in the U.S.’ Cigarette smoking is linked to a number of diseases, most notably coronary heart disease and lung cancer, and is responsible for more than 300,000 deaths each year in the Despite these problems, a review of previous research by Bonaguro and Bonaguro3 indicates that more than 50 million Americans smoke, including an esimated 3.2 million public school students. Other reports document cigarette smoking rates among adolescents as well.‘ Smoking prevalence in the U.S. decreased from 36.7% in 1976 to 30.4% in 1985. In 1986, 18.7% of high school seniors reported daily use of cigarettes, a significant decline from 1976 when 26.8% reported daily use.5 Despite this decline, cigarettes remain the most prevalent drug used during adolescence.6 Each day, more than 3,000 American teen-agers start smoking. Results from the National Adolescent Student Health Survey’ showed that one in five adolescents reported smoking cigarettes during the previous month. This same study showed that 5 1070 of eighth grade students and 63% of 10th grade students had tried smoking. In all, 16% of eighth grade students and 26% of ~
~~~
Robert J. McDermott, PhD. FASHA; Phillip J. Marty, PhD. CHES; and Eileen M. Emery, MPH, CHES, University of South Florida, College of Public Health, Dept. of Community and Family Health. Tompo, FL 33612; Paul D. Sarvela, PhD, CHES, Dept. of Health Education, Southern Illinois University at Carbondale, Carbondale, IL 62901; Srijrno M. Bajrocharya. PhD, University of Maine at Presque Isle, Presque Isle. ME 04769; and Pamela N. Hoalt, PhD, Dept. of Health, Physicol Education, and Recreation, Western Michigon University, Kalamazoo, MI 49008. This orticle was submitted October 11. 1991. ond revised and accepted for publication Morch 2, 1992.
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10th grade students had smoked cigarettes in the past month. A greater proportion of adolescent females than males report use, a fact that suggests adolescent females have more vulnerability toward influences which encourage sm0king.O Some investigators suggest high school males may have a larger arsenal of deviant behaviors which can be adopted than their female counterp a r t ~ Cigarette .~ smoking may be females’ most practical or visible manner in which to rebel. Some literature corroborates influences such as low self-esteem, need for recognition and independence, and desire to appear mature.lOJ1Behavioral intention to smoke also provides a good predictor of later smoking status.O Two major sources of influence to begin smoking come from peers and family. One study” reported that, among adolescents having both parents and best friends who smoked, only 11070 had never smoked and 24% were frequent smokers. In contrast, among adolescents whose parents and best friends were non-smokers, 8Ov0 had never smoked, and only 3% were regular smokers. In addition to peer and parental examples, parental attitude appears important in moderating smoking behavior among adolescents. Newman and Wardt3 suggest that regardless of parental smoking behavior, an expressed attitude can influence smoking. They further state that parents may neglect expressing an anti-smoking message to their children thinking that society’s message against smoking is clear and of sufficient magnitude. Adolescent smoking is a complex behavior. Because of the complexity induced by many variables that influence cigarette use, a need exists to investigate more than one variable at a time. Furthermore, data on cigarette smoking initiation and use during adolescence by var-
ious U.S. ethnic groups are limited.“ This study examined multiple correlates of cigarette use among adolescents in a statistical model that considered interaction among demograpic and other variables under study.
METHOD Subjects
The study population consisted of 2,425 students present on enrollment rosters during December 1988 in either of two large rural high schools (grades 10-12) in west central Florida. The study sample consisted of students in attendance on the day a tobacco use inventory was administered, and whose responses were sufficiently complete to be included in the data base (n = 2,212). The final sample included 91.2% of the combined enrollment at the two schools. Male and female composition of the sample was 42% and 58070, respectively. Concerning grade level breakdown: 32.6% were 10th grade students, 36.2% 11th grade students, and 30.5% 12th grade students. With regard to ethnic composition, 86.3% were Caucasian, 10.3% were African-American, 2.5% were Hispanic, and the remaining 0.9% were “other. ” Research Design
A cross-sectional survey research design involving self-report was used for the study. This design was chosen because it enables gathering a large amount of data from people in a relatively brief period of time.lJ While the utility of self-report instruments for tobacco use research is sometimes criticized, numerous studies support their validity and reliability.12J619 Cost and time issues, logistics of receiving administrative endorsement and cooperation, and school district requirements for active parental consent prohibited use of corroborating measures such as serum thiocyanate,20saliva thiocyanate,” expired carbon monoxide,” blood cotinine,“ or bogus pipeline.22 Instrumentation
Two instruments were used in this study: a self-report tobacco use inventory (TUI) developed for this study, and the Hare Self-Esteem Scale.23The initial pool of items for the TUI included 57 questions generated from a literature review which focused on cigarette smoking among American youth. Pilot-testing for face validity, clarity of directions, and overall readability was carried out on a separate sample of 10th and 11th grade students (n = 52). Concurrent with this process, content validity reviews were carried out by a panel of eight persons: five university health educators involved in tobacco use research, two high school teachers of life management skills, and one school district official responsible for supervising health education. After consolidation of items and other modifications based on these reviews, the final 44-item instrument was organized to focus on the following tobacco use variables: personal use of cigarettes, reasons for initiation, continuation, and cessation, peer and family use of cigarettes, health beliefs toward cigarette use, attitudes toward cigarette smokers, smokeless tobacco use, marijuana use, alcohol use, and selected demographic variables. At this stage, additional content review was
carried out by two university health educators, but yielded no further modification of a substantive nature. A readability test using the SMOGz4procedure estimated the reading level of the TUI between seventh and eighth grade. Reliability of the TUI was measured using test-retest procedures. Test-retest results were based on examining a cluster of 46 students (39 from whom both test and retest scores could be obtained) 12 days apart. For categorical variables, the percentage agreement approach was used, which yielded an average agreement of 93.5% from TI to TI. Continuous variables were measured using the Pearson product-moment correlation coefficient. Test-retest reliability coefficients for all such variables were .70 or greater. On the basis of readability, content validation, and reliability assessments, the instrument was considered appropriate for selfreport measurement of tobacco use by youth in the targeted age group. Since self-esteem has been hypothesized as a factor in smoking initiation d e c i s i ~ n , ~ Jthe ~ J other ~ * ~ ~major instrument employed in this investigation was the Hare Self-Esteem Scale, a 30-item, self-report, area-specific scale with subcales for peer, school, and home selfesteem.” Items are scored on a four-point scale ranging from strongly agree to strongly disagree. Subscale scores range from a low of 10 to a high of 40.Construct validity of the Hare Self-Esteem Scale has been established in previous studies.z6The scale was selected for this investigation due to its low cost, its relatively simple administration, its specificity to three areas theoretically important in health behavior decisions, and previous related research that has employed the scale successfully.23-u~26 Internal consistency of each subscale for the study sample was estimated used Cronbach’s alpha, and produced values of a = .74 (peer), a = .61 (family), and a = .79 (school). Readability testing using the SMOG” formula indicates the Hare Self-Esteem Scale has a reading level between sixth and seventh grade. Since the Hare Self-Esteem Scale has been used with a wide range of ages of schoolchildren,2*its audience appropriateness for the study also seemed acceptable. Procedures
Data Collection Procedures. Prior to data collection, the study was approved by two institutional review boards (IRBs) on human subjects research. One IRB was from the university which initiated the research; the other IRB was that of the participating school district. Associates of the primary investigators, thoroughly prepared in survey data collection techniques, were present for instrument administration. Prior to administering the instrument, human subjects requirements were addressed, and explicit instructions for completion of the inventory were provided. Proctors assisted respondents, if necessary, in identifying the category of tobacco use that best described them. The inventory required about 25 minutes to complete. Standard descriptive procedures were applied to all study variables in the initial analysis. A two-stage multiple regression analysis followed. The initial regression analysis examined relationships among 21 predictor variables and the criterion (cigarette use). Upon completion of the initial regression procedures, all variables
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classify themselves without difficulty.
were examined for their levels of significance. Those variables with a p value of .01 or less then were used in the second regression analysis. Nine of the original 21 variables met the .01 level of significance criterion. A frequent difficulty in comparing prevalence of smoking across studies involves the different approaches used to define a smoker and how much one smokes. This study adopted some conventional definitions yet modified them to permit not only categorization of respondents as smokers or non-smokers, but to categorize smokers according to level of smoking. The never smoker either never even tried smoking a cigarette, or use was limited to a few instances, and who had no future intention of smoking. The occasional smoker had smoked at least 100 cigarettes in a lifetime, planned to continue smoking, but whose current smoking activity was less than daily. Ex-smokers estimated their lifetime cigarette smoking consumption to have been at least 100, had not smoked in the past 30 days, and who had no future intention of smoking. Regular smokers were daily smokers classified four ways: 5 10 cigarettes per day, 11-20 cigarettes per day, 21-40 cigarettes per day, and more than 40 cigarettes per day. Though it can be argued that categories may not be mutually exclusive, or that some smokers might not fit these labels such as a recently initiated smoker who smokes less than daily, has smoked fewer than 100 cigarettes, but who plans to continue indefinitely, virtually all respondents could
RESULTS Analysis of the cigarette use variable indicated 8.9% of the sample smoked cigarettes occasionally, while an additional 5.3% reported they smoked daily. Among daily smokers, about 41.2% reported smoking 11 or more cigarettes per day. In addition to persons who reported current smoking activity, approximately 12.8% indicated they were ex-smokers. Across all smoking classifications, males and females smoked at almost equal rates, and 10th grade students smoked at slightly higher rates (16.4%) than upperclassmen (1 1.8% of 1 lth grade students and 13.9% of 12th grade students). With regard to ethnic background, persons who identified themselves as “other” smoked at the greatest level, followed by Hispanic, Caucasian, and African-American groups. These data are summarized in Table 1. The initial multiple regression analysis used 21 variables to predict cigarette smoking in this group. Variables included in this analysis were subscales of the Hare Self-Esteem Scale, peer and family use of cigarettes, health beliefs toward cigarette use, attitude toward cigarette smokers, smokeless tobacco use, marijuana use, alcohol use, and demographic variables. After the initial analysis, variables with significance levels of .01 or less were entered into the second equation. These variables were ethnicity, school self-esteem,
Table 1 Descriptive Summary of Cigarette Use (94) I10
Ex-smoker
N
Total Male Female 10th grade 11th grade lah grade
Black White Hispanic Other
Never smoked
Smoked
cl~mllos
occtslorlly
Idly
/dry
> 40 clyretta: /day
11-20
21-40
clgafotla: /day
cl(pnttts
2,188
12.8
72.9
8.9
2.8
1.6
0.5
0.4
914 1.274
12.7 12.9
72.9 73.2
9.4 8.6
2.8 2.8
1.1 2.0
0.7 0.2
0.4 0.3
718 796 662
13.7 13.1 11.5
69.9 75.1 74.6
11.7 7.5 7.6
2.5 3.0 3.0
2.2 0.8 1.8
0.0 0.3 0.9
0.0 0.3 0.6
230 1.882 54 22
6.1 13.6 18.5 0.0
90.4 71.4 59.3 54.6
2.6 9.8 7.4 9.1
0.0 3.0 11.1 0.0
0.9 1.8 0.0 0.0
0.0 0.3 3.7 18.2
0.0 0.1 0.0 18.2
Table 2 Multiple Regression Results of Ciuarette Use ANOVA OF 9 1866
Regression Residual
F= 83.50 Multiple R = ,534 Standard Error = .66
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Moan Squarer
330.61 820.88
36.73 .44
Slg. F = .OOOO Adjusted R Square = .28
B
Varlrble School self-esteem Marijuana use Black Hispanic Best trlend’s use Alcohol use Attitudes towards female use Close friends’ use White (Constant)
148
Sum ol Squans
.01 .12 -1.16 -1.17 .14 .06 .20
.02 -1.17 2.37
April 1992, Vol. 62, No. 4
SE B
.00 .02 .15 .17 .04 .02 .01
.oo
.14 .19
Beta .06 .ll -.43 -.24 .07 .07 .32 .15 -.51
1 3.10 5.38 -7.84 -7.000 3.21 3.24 14.64 6.53 -8.44 12.73
810. ,0020
.oooo .OOOO
.oooo ,0013 ,0012
.om0
.oooo .oooo
.woo
personal use of marijuana, close friends’ cigarette smoking, personal use of alcohol, attitude toward smoking by females, and best friend’s cigarette smoking. Results from the second regression analysis suggested all these variables were related significantly to cigarette smoking. The multiple R (coefficient of multiple correlation) was 3 4 , while the adjusted R2 (coefficient of determination) was .28. Examination of beta weights shows strong negative betas for the ethnic variables, while the individual’s attitude toward females’ smoking of cigarettes was the most powerful positive beta weight (Table 2).
DISCUSSION While about 14.3% of subjects considered themselves at least occasional smokers, only 5.3% smoked on a daily basis. Only 16.4% of 10th grade students were current smokers at any level compared to 26% reported in the National Adolescent Student Health Survey.’ These data revealed just 6.3% of 12th grade students to be daily smokers, compared to 18.7% reported by the U.S. Dept. of Health and Human Services.’ Thus, the reported level of smoking in this sample was much less than observed in national studies. Of further note is that 12.8% of the sample reported they were ex-smokers. These figures provide evidence for the notion that anti-smoking messages may be helping young people decide to quit or avoid extended involvement with cigarettes. From their Minnesota/North Dakota data, Perry, Murray, and KleppZ9suggested cigarette smoking may have a certain functionality for some adolescents such as a coping mechanism for boredom or a strategy for stress reduction. A greater percentage of females smoked daily (5.3% vs. 5.0%), while males reported slighty more overall smoking activity (14.4% vs. 13.9%). According to Bloch, cited in Cotton,’O national figures for high school seniors reveal that 20% of females and 16% of males smoke at some level. Data from this study suggest that schools consider local conditions, customs, cultures, and other influences in planning and implementing tobacco curricula. A prevention and intervention program that is generic, vaguely targeted, or does not take local conditions into account may have an impact that is less than optimal. Interestingly, 10th grade students smoked at the highest levels of all studied. Perhaps at the 10th grade level, peer pressure to smoke is higher than at other grade levels. An evaluation of the Teenage Health Teaching Modules speculated that junior high school students might be more resistant to anti-tobacco use message^.^^ Perhaps the greater involvement with tobacco by the 10th grade subsample in this study reflects residual effects of a similar phenomenon. School and community health education programs may begin to show modest effects by the 1lth and 12th grades in this population. Data from Errecart et al” seem to support this contention. If this inference is accurate, health promoting, anti-tobacco use messages should be maintained and reinforced by health educators throughout the high school years. In a study of substance use among elementary and middle schoolchildren in which the area-specific Hare
Self-Esteem Scale was used concurrently, Young et alZ1 found both school self-esteem and home self-esteem related inversely to current substance use and future intention to use. Much research that relates gateway drug use to self-esteem considers this latter construct as a unitary measure. These results from the current study corroborate those of Young, et a P with respect to school self-esteem, and confirm the utility of an areaspecific instrument. Though the school self-esteem subscale variable was not the most powerful element of the regression model, it was a statistically significant component nevertheless. The other subscales (peer and home) did not enter significantly in the regression model. Thus, health educators and other specialists working at the secondary school level should focus their attention on school self-esteem in prevention programming rather than on more generic measures of selfesteem that correlate only weakly with substance abuse. 32 The ethnicity variable showed interesting patterns of response. Respondents classifying themselves as “other” reported the most smoking activity, 36.4% of the “other” sample smoked 21 or more cigarettes per day. Of the identifiable ethnic groups, Hispanics had the highest rate (22.2%), followed by the Caucasian group (15%). The lowest smoking rate by ethnic group was among African-Americans, where 3.5% indicated they smoked at least occasionally. The more parsimonious regression model was comprised of the following variables (presented in order of strength of beta weights): ethnic group, attitude toward females who smoke, close friends’ smoking, personal use of marijuana, best friend’s smoking, personal use of alcohol, and the Hare subscale for school self-esteem. When these variables were entered into the regression model, ethnic variables became the strongest predictors of cigarette use, while close friends’ and best friend’s use, alcohol use, and marijuana use, had more modest beta weights. This observation suggests that for this sample, a strong moderating effect exists between ethnic characteristics and peer use. These ethnic variables collectively were the best demographic predictor of tobacco use. This pattern of cigarette use shows possible ethnic patterns which should be considered in future health education program development. For example, it may be necessary to develop smoking education programs culturally sensitive to Hispanic groups, to employ positive role models salient to selected cultural groups, and to develop materials written or presented in Spanish since almost one-fourth of the Hispanic students sampled here reported smoking at least occasionally. Intrepretation must be cautious, however, since the actual number of respondents in this study who identified themselves as Hispanic was small. However, data from larger studies support a need for programs to include a special ethnic or cultural sensitivity. Examination of the National Health Interview Survey data and the Hispanic Health and Nutrition Survey data by Escobedo et all4 showed that Mexican-American males, Puerto Rican-American males, and Cuban-American males -c age 18 all had smoking initiation rates higher than their non-Hispanic peers. The pattern among females, while not as pronounced, was nevertheless
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apparent. As has been suggested by other investigators,” additional factors, such as differential familial organization, unique historical/cultural milieus, reactions to societal labeling, socioeconomic status, and reading level influences on survey responses may have a mediating or interactive effect with respect to ethnicity. Another issue which may be surfacing here is that peer use of a substance, which was a good predictor of substance use in certain populations such as middle school students, may no longer be a good predictor,” because at this age, students are less interested in, or less influenced by, perceptions of their peer group’s expectations. Further research concerning peer interaction and influence may disclose more information concerning this uncertainty. References I . Penner M. Economic incentives to reduce employee smoking: A health insurance surcharge for tobacco using State of Kansas employees. A m J Health Promotion. 1989;4(1):5-11. 2 . US Dept of Health and Human Services. The Health Consequences of Smoking: Nicotine addiction. A report to the surgeon general. Washington, DC: Public Health Service, Centers for Disease Control, Center for Health Promotion and Education, Office on Smoking and Health; 1988. 3. Bonaguro EW, Bonaguro JA. Tobacco use among adolescents: Directions for research. A m J Health Promotion. 1989;4(1):3741. 4. Pierce JP, Fiore MC, Novotny TE, Hatziandreu EJ, Davis RM. Trends in cigarette smoking in the United States: Projections to the year 2OOO. JAMA. 1989;261:61-65. 5 . US Dept of Health and Human Services: Reducing the Health Consequences of Smoking: 25 years of progress. A report of the surgeon general. Rockville, Md: Office of Smoking and Health DDHS publication no CDC 89-8411; 1989. 6. Landers C, Orlandi, MA. Why do teenagers smoke and chew. Educ Horizons. 1987;65(3):133-134. 7. National Adolescent Student Health Survey: A report on the health of American youth. Kent, Ohio: American School Health Association; 1988. 8. Clarke JH. Reducing adolescent smoking: A comparison of peer-led, teacher-led, and expert interventions. J Sch Health. 1986;5 (3):102-106. 9. Krohn MD, Naughton MJ, Skinner WF, Becker SL, Lauer RM. Social disaffection, friendship patterns and adolescent cigarette use: The Muscatine Study. J Sch Health. 1986;56(3):146-150. 10. Dielman T, Leech S,Larenger A, Horvath W. Health locus of control and self-esteem as related to adolescent behavior and intentions. Adolescence. 1984; 19(76):935-950. 1 1 . Tucker L. Physical, psychological, social and lifestyle differences among adolescents classified according to cigarette intention status. J Sch Health. 1985;55(4):127-130. 12. Lauer RM, Akers RL, Massey J, Clarke WR. Evaluation of cigarette smoking among adolescents: The Muscatine Study. Prev Med. 1982;11:417428. 13. Newman IM, Ward JMW. The influence of parental attitude and behavior on early adolescent cigarette smoking. J Sch Health.
198%59(4):150-152. 14. Escobedo LO, Anda RF, Smith PF. Remington PL, Mast EE. Sociodemographic characteristics of cigarette smoking initiation in the United States. JAMA. 1990,264:1550-1555. 15. Windsor RA, Baranowski T, Clark N, Cutter G. Evaluation of Health Promotion and Education Programs. Palo Alto, Calif: Mayfield, 1984. 16. Akers RL, Massey J, Clarke W. Lauer RM. Are self-reports of adolescent deviance valid? Biochemical measures, randomized response, and the bogus pipeline in smoking behavior. Social Forces. 1983;62:234-251. 17. Bauman KE, Koch GG, Bryan ES. Validity of self-reports of adolescent cigarette smoking. Intemat J Addict. 1982;17:1131-1136. 18. Luepker RV, Pallonen UE, Murray DM, Pirie PL. Validity of telephone surveys in assessing cigarette smoking in young adults. Am J Public Health. 1989;79:202-204. 19. Slattery ML, Hunt SC, French TK, Ford HM, Williams RR. Validity of cigarette smoking habits in three epidemiologic studies in Utah. Prev Med. 1989;18:11-19. 20. Farquhar TW, Wood PD, Breitose H, Haskell WL, Meyer AJ, Maccoby N, et al. Community education for cardiovascular health. Lancet. 1977;1(8023):1192-1195. 21. Pechacek TF, Murray DM, Luepker RV, Mittlemark MB, Johnson CA, Shutz JM. Measurement of adolescent smoking behavior: Rationale and methods. J Eehav Med. 1984;11:191-203. 22. Werch CE, Gorman DR, Marty PJ, Forbess J , Brown B. Effects of the bogus-pipeline on enhancing self-reported adolescent drug use measures. J Sch Health. 1987;57(6):232-236. 23. Hare BR. Racial and socioeconomic variations in preadolescent area-specific and general self-esteem. Internal J Int Re/. 1977;1(3): 31-51. 24. McLaughlin OH: SMOG grading - a new readability formula. J Read. 1%9;12:639-646. 25. Semmer NY, Cleary PD, Dwyer JH, Fuchs R, Lippert P. Psychosocial predictors of adolescent smoking in two German cities: The Berlin-Breman Study. MMWR. 1987;36(Supple 4):3-10. 26. Schoemaker AL. Construct validity of area specific self-esteem: The Hare Self-Esteem Scale. Educ & Psycho1 Measure. 1980;40:495-501. 27. Young M. Self-esteem and sexual behavior among early adolescents. Fam Life Educ. 1989;7(4):16-19. 28. Young M, Werch CE, Bakema D: Area specific self-esteem scales and substance use among elementary and middle school children. J Sch Health. 1989;59(6):251-254. 29. Perry CL, Murray DM, Klepp K-I. Predictors of adolescent smoking and implications for prevention. MMWR. 1987;36(Suppl): 4145. 30. Cotton P. Tobacco foes attack ads that target women, minorities, teens, and the poor. JAMA. 1990;264:1505-1506. 31. Errecart MT, Walberg HJ, Ross JG, Gold RS, Fiedler JL, Kolbe LJ. Effectiveness of teenage health teaching modules. J Sch Health. 1991 ;61(1):26-30. 32. Botvin GJ. Substance abuse prevention research: Recent developments and future directions. J Sch Health. 1986;56(9):369-374. 33. Sussman S, Dent CW, Flay BR, Hansen WB, Johnson CA. Psychosocial predictors of cigarette smoking onset by White, Black, Hispanic, and Asian adolescents in southern California. MMWR. 1987;36(S~ppl): 11-16. 34. Sarvela PD, McClendon EJ. Indicators of rural youth drug use. J Youth & A d d . 1988;17(4):337-349.
Smoking and Tobacco Control - The National Cancer Institute has begun a new series of scientific monographs on smoking and tobacco control. The first monograph - Strategies to Control Tobacco Use in the United States: A blueprint for public health action in the 1990s includes topics such as the evolution of smoking control strategies and evidence of their need based on the increase in smoking prevalence and lung cancer death rates. The second monograph - Tobacco and the Clinician: Interventionsfor medical and dental practices will discuss intervention methods that have been successful and ways to expand and improve these interventions through a national program. To receive a copy of the first monograph and to be placed on the mailing list for future copies, contact: Donald R. Shopland, Smoking and Tobacco Control Coordinator, National Cancer Institute, EPN Room 241, 9ooo Rockville Pike, Bethesda, MD 20892.
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ABSTRACT: A cross-sectional survey research design measured factors related to cigarette use among 2,212 senior high school students. Results showed 14.3% of the sample smoked cigarettes at leost occasionally, with 5.3% reporting they were doily smokers. About 12.8% indicated they were ex-smokers. Males ond females smoked at almost equal rates. and the percentage of 10th grade student smokers was slightly higher (16.4%) than the percentage of juniors and seniors who smoked. Approximately 22% of Hispanic students, 15% of Caucasian students, and 4.5% of African-American students reported smoking cigorettes at least occasionally. An initial regression analysis used 21 variables to predict cigorette smoking. A more parsimonious regression model (R’ = .28), using varioblesfrom the initial regression onalysis with significance levels of .01 or less, indicated the most important predictors of cigorelte use were ethnic group, ottitude toward femoles who smoke, close friends’ use of cigarettes, personal use of marguano, best friend’s use of cigarettes, personal use of alcohol, and school selfesteem. Implications for school health programs ore addressed. ( J Sch Health. 1992;62(4): 146-150)
R
esearch confirms smoking as the most important preventable cause of morbidity and mortality in the U.S.’ Cigarette smoking is linked to a number of diseases, most notably coronary heart disease and lung cancer, and is responsible for more than 300,000 deaths each year in the Despite these problems, a review of previous research by Bonaguro and Bonaguro3 indicates that more than 50 million Americans smoke, including an esimated 3.2 million public school students. Other reports document cigarette smoking rates among adolescents as well.‘ Smoking prevalence in the U.S. decreased from 36.7% in 1976 to 30.4% in 1985. In 1986, 18.7% of high school seniors reported daily use of cigarettes, a significant decline from 1976 when 26.8% reported daily use.5 Despite this decline, cigarettes remain the most prevalent drug used during adolescence.6 Each day, more than 3,000 American teen-agers start smoking. Results from the National Adolescent Student Health Survey’ showed that one in five adolescents reported smoking cigarettes during the previous month. This same study showed that 5 1070 of eighth grade students and 63% of 10th grade students had tried smoking. In all, 16% of eighth grade students and 26% of ~
~~~
Robert J. McDermott, PhD. FASHA; Phillip J. Marty, PhD. CHES; and Eileen M. Emery, MPH, CHES, University of South Florida, College of Public Health, Dept. of Community and Family Health. Tompo, FL 33612; Paul D. Sarvela, PhD, CHES, Dept. of Health Education, Southern Illinois University at Carbondale, Carbondale, IL 62901; Srijrno M. Bajrocharya. PhD, University of Maine at Presque Isle, Presque Isle. ME 04769; and Pamela N. Hoalt, PhD, Dept. of Health, Physicol Education, and Recreation, Western Michigon University, Kalamazoo, MI 49008. This orticle was submitted October 11. 1991. ond revised and accepted for publication Morch 2, 1992.
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10th grade students had smoked cigarettes in the past month. A greater proportion of adolescent females than males report use, a fact that suggests adolescent females have more vulnerability toward influences which encourage sm0king.O Some investigators suggest high school males may have a larger arsenal of deviant behaviors which can be adopted than their female counterp a r t ~ Cigarette .~ smoking may be females’ most practical or visible manner in which to rebel. Some literature corroborates influences such as low self-esteem, need for recognition and independence, and desire to appear mature.lOJ1Behavioral intention to smoke also provides a good predictor of later smoking status.O Two major sources of influence to begin smoking come from peers and family. One study” reported that, among adolescents having both parents and best friends who smoked, only 11070 had never smoked and 24% were frequent smokers. In contrast, among adolescents whose parents and best friends were non-smokers, 8Ov0 had never smoked, and only 3% were regular smokers. In addition to peer and parental examples, parental attitude appears important in moderating smoking behavior among adolescents. Newman and Wardt3 suggest that regardless of parental smoking behavior, an expressed attitude can influence smoking. They further state that parents may neglect expressing an anti-smoking message to their children thinking that society’s message against smoking is clear and of sufficient magnitude. Adolescent smoking is a complex behavior. Because of the complexity induced by many variables that influence cigarette use, a need exists to investigate more than one variable at a time. Furthermore, data on cigarette smoking initiation and use during adolescence by var-
ious U.S. ethnic groups are limited.“ This study examined multiple correlates of cigarette use among adolescents in a statistical model that considered interaction among demograpic and other variables under study.
METHOD Subjects
The study population consisted of 2,425 students present on enrollment rosters during December 1988 in either of two large rural high schools (grades 10-12) in west central Florida. The study sample consisted of students in attendance on the day a tobacco use inventory was administered, and whose responses were sufficiently complete to be included in the data base (n = 2,212). The final sample included 91.2% of the combined enrollment at the two schools. Male and female composition of the sample was 42% and 58070, respectively. Concerning grade level breakdown: 32.6% were 10th grade students, 36.2% 11th grade students, and 30.5% 12th grade students. With regard to ethnic composition, 86.3% were Caucasian, 10.3% were African-American, 2.5% were Hispanic, and the remaining 0.9% were “other. ” Research Design
A cross-sectional survey research design involving self-report was used for the study. This design was chosen because it enables gathering a large amount of data from people in a relatively brief period of time.lJ While the utility of self-report instruments for tobacco use research is sometimes criticized, numerous studies support their validity and reliability.12J619 Cost and time issues, logistics of receiving administrative endorsement and cooperation, and school district requirements for active parental consent prohibited use of corroborating measures such as serum thiocyanate,20saliva thiocyanate,” expired carbon monoxide,” blood cotinine,“ or bogus pipeline.22 Instrumentation
Two instruments were used in this study: a self-report tobacco use inventory (TUI) developed for this study, and the Hare Self-Esteem Scale.23The initial pool of items for the TUI included 57 questions generated from a literature review which focused on cigarette smoking among American youth. Pilot-testing for face validity, clarity of directions, and overall readability was carried out on a separate sample of 10th and 11th grade students (n = 52). Concurrent with this process, content validity reviews were carried out by a panel of eight persons: five university health educators involved in tobacco use research, two high school teachers of life management skills, and one school district official responsible for supervising health education. After consolidation of items and other modifications based on these reviews, the final 44-item instrument was organized to focus on the following tobacco use variables: personal use of cigarettes, reasons for initiation, continuation, and cessation, peer and family use of cigarettes, health beliefs toward cigarette use, attitudes toward cigarette smokers, smokeless tobacco use, marijuana use, alcohol use, and selected demographic variables. At this stage, additional content review was
carried out by two university health educators, but yielded no further modification of a substantive nature. A readability test using the SMOGz4procedure estimated the reading level of the TUI between seventh and eighth grade. Reliability of the TUI was measured using test-retest procedures. Test-retest results were based on examining a cluster of 46 students (39 from whom both test and retest scores could be obtained) 12 days apart. For categorical variables, the percentage agreement approach was used, which yielded an average agreement of 93.5% from TI to TI. Continuous variables were measured using the Pearson product-moment correlation coefficient. Test-retest reliability coefficients for all such variables were .70 or greater. On the basis of readability, content validation, and reliability assessments, the instrument was considered appropriate for selfreport measurement of tobacco use by youth in the targeted age group. Since self-esteem has been hypothesized as a factor in smoking initiation d e c i s i ~ n , ~ Jthe ~ J other ~ * ~ ~major instrument employed in this investigation was the Hare Self-Esteem Scale, a 30-item, self-report, area-specific scale with subcales for peer, school, and home selfesteem.” Items are scored on a four-point scale ranging from strongly agree to strongly disagree. Subscale scores range from a low of 10 to a high of 40.Construct validity of the Hare Self-Esteem Scale has been established in previous studies.z6The scale was selected for this investigation due to its low cost, its relatively simple administration, its specificity to three areas theoretically important in health behavior decisions, and previous related research that has employed the scale successfully.23-u~26 Internal consistency of each subscale for the study sample was estimated used Cronbach’s alpha, and produced values of a = .74 (peer), a = .61 (family), and a = .79 (school). Readability testing using the SMOG” formula indicates the Hare Self-Esteem Scale has a reading level between sixth and seventh grade. Since the Hare Self-Esteem Scale has been used with a wide range of ages of schoolchildren,2*its audience appropriateness for the study also seemed acceptable. Procedures
Data Collection Procedures. Prior to data collection, the study was approved by two institutional review boards (IRBs) on human subjects research. One IRB was from the university which initiated the research; the other IRB was that of the participating school district. Associates of the primary investigators, thoroughly prepared in survey data collection techniques, were present for instrument administration. Prior to administering the instrument, human subjects requirements were addressed, and explicit instructions for completion of the inventory were provided. Proctors assisted respondents, if necessary, in identifying the category of tobacco use that best described them. The inventory required about 25 minutes to complete. Standard descriptive procedures were applied to all study variables in the initial analysis. A two-stage multiple regression analysis followed. The initial regression analysis examined relationships among 21 predictor variables and the criterion (cigarette use). Upon completion of the initial regression procedures, all variables
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classify themselves without difficulty.
were examined for their levels of significance. Those variables with a p value of .01 or less then were used in the second regression analysis. Nine of the original 21 variables met the .01 level of significance criterion. A frequent difficulty in comparing prevalence of smoking across studies involves the different approaches used to define a smoker and how much one smokes. This study adopted some conventional definitions yet modified them to permit not only categorization of respondents as smokers or non-smokers, but to categorize smokers according to level of smoking. The never smoker either never even tried smoking a cigarette, or use was limited to a few instances, and who had no future intention of smoking. The occasional smoker had smoked at least 100 cigarettes in a lifetime, planned to continue smoking, but whose current smoking activity was less than daily. Ex-smokers estimated their lifetime cigarette smoking consumption to have been at least 100, had not smoked in the past 30 days, and who had no future intention of smoking. Regular smokers were daily smokers classified four ways: 5 10 cigarettes per day, 11-20 cigarettes per day, 21-40 cigarettes per day, and more than 40 cigarettes per day. Though it can be argued that categories may not be mutually exclusive, or that some smokers might not fit these labels such as a recently initiated smoker who smokes less than daily, has smoked fewer than 100 cigarettes, but who plans to continue indefinitely, virtually all respondents could
RESULTS Analysis of the cigarette use variable indicated 8.9% of the sample smoked cigarettes occasionally, while an additional 5.3% reported they smoked daily. Among daily smokers, about 41.2% reported smoking 11 or more cigarettes per day. In addition to persons who reported current smoking activity, approximately 12.8% indicated they were ex-smokers. Across all smoking classifications, males and females smoked at almost equal rates, and 10th grade students smoked at slightly higher rates (16.4%) than upperclassmen (1 1.8% of 1 lth grade students and 13.9% of 12th grade students). With regard to ethnic background, persons who identified themselves as “other” smoked at the greatest level, followed by Hispanic, Caucasian, and African-American groups. These data are summarized in Table 1. The initial multiple regression analysis used 21 variables to predict cigarette smoking in this group. Variables included in this analysis were subscales of the Hare Self-Esteem Scale, peer and family use of cigarettes, health beliefs toward cigarette use, attitude toward cigarette smokers, smokeless tobacco use, marijuana use, alcohol use, and demographic variables. After the initial analysis, variables with significance levels of .01 or less were entered into the second equation. These variables were ethnicity, school self-esteem,
Table 1 Descriptive Summary of Cigarette Use (94) I10
Ex-smoker
N
Total Male Female 10th grade 11th grade lah grade
Black White Hispanic Other
Never smoked
Smoked
cl~mllos
occtslorlly
Idly
/dry
> 40 clyretta: /day
11-20
21-40
clgafotla: /day
cl(pnttts
2,188
12.8
72.9
8.9
2.8
1.6
0.5
0.4
914 1.274
12.7 12.9
72.9 73.2
9.4 8.6
2.8 2.8
1.1 2.0
0.7 0.2
0.4 0.3
718 796 662
13.7 13.1 11.5
69.9 75.1 74.6
11.7 7.5 7.6
2.5 3.0 3.0
2.2 0.8 1.8
0.0 0.3 0.9
0.0 0.3 0.6
230 1.882 54 22
6.1 13.6 18.5 0.0
90.4 71.4 59.3 54.6
2.6 9.8 7.4 9.1
0.0 3.0 11.1 0.0
0.9 1.8 0.0 0.0
0.0 0.3 3.7 18.2
0.0 0.1 0.0 18.2
Table 2 Multiple Regression Results of Ciuarette Use ANOVA OF 9 1866
Regression Residual
F= 83.50 Multiple R = ,534 Standard Error = .66
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Moan Squarer
330.61 820.88
36.73 .44
Slg. F = .OOOO Adjusted R Square = .28
B
Varlrble School self-esteem Marijuana use Black Hispanic Best trlend’s use Alcohol use Attitudes towards female use Close friends’ use White (Constant)
148
Sum ol Squans
.01 .12 -1.16 -1.17 .14 .06 .20
.02 -1.17 2.37
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SE B
.00 .02 .15 .17 .04 .02 .01
.oo
.14 .19
Beta .06 .ll -.43 -.24 .07 .07 .32 .15 -.51
1 3.10 5.38 -7.84 -7.000 3.21 3.24 14.64 6.53 -8.44 12.73
810. ,0020
.oooo .OOOO
.oooo ,0013 ,0012
.om0
.oooo .oooo
.woo
personal use of marijuana, close friends’ cigarette smoking, personal use of alcohol, attitude toward smoking by females, and best friend’s cigarette smoking. Results from the second regression analysis suggested all these variables were related significantly to cigarette smoking. The multiple R (coefficient of multiple correlation) was 3 4 , while the adjusted R2 (coefficient of determination) was .28. Examination of beta weights shows strong negative betas for the ethnic variables, while the individual’s attitude toward females’ smoking of cigarettes was the most powerful positive beta weight (Table 2).
DISCUSSION While about 14.3% of subjects considered themselves at least occasional smokers, only 5.3% smoked on a daily basis. Only 16.4% of 10th grade students were current smokers at any level compared to 26% reported in the National Adolescent Student Health Survey.’ These data revealed just 6.3% of 12th grade students to be daily smokers, compared to 18.7% reported by the U.S. Dept. of Health and Human Services.’ Thus, the reported level of smoking in this sample was much less than observed in national studies. Of further note is that 12.8% of the sample reported they were ex-smokers. These figures provide evidence for the notion that anti-smoking messages may be helping young people decide to quit or avoid extended involvement with cigarettes. From their Minnesota/North Dakota data, Perry, Murray, and KleppZ9suggested cigarette smoking may have a certain functionality for some adolescents such as a coping mechanism for boredom or a strategy for stress reduction. A greater percentage of females smoked daily (5.3% vs. 5.0%), while males reported slighty more overall smoking activity (14.4% vs. 13.9%). According to Bloch, cited in Cotton,’O national figures for high school seniors reveal that 20% of females and 16% of males smoke at some level. Data from this study suggest that schools consider local conditions, customs, cultures, and other influences in planning and implementing tobacco curricula. A prevention and intervention program that is generic, vaguely targeted, or does not take local conditions into account may have an impact that is less than optimal. Interestingly, 10th grade students smoked at the highest levels of all studied. Perhaps at the 10th grade level, peer pressure to smoke is higher than at other grade levels. An evaluation of the Teenage Health Teaching Modules speculated that junior high school students might be more resistant to anti-tobacco use message^.^^ Perhaps the greater involvement with tobacco by the 10th grade subsample in this study reflects residual effects of a similar phenomenon. School and community health education programs may begin to show modest effects by the 1lth and 12th grades in this population. Data from Errecart et al” seem to support this contention. If this inference is accurate, health promoting, anti-tobacco use messages should be maintained and reinforced by health educators throughout the high school years. In a study of substance use among elementary and middle schoolchildren in which the area-specific Hare
Self-Esteem Scale was used concurrently, Young et alZ1 found both school self-esteem and home self-esteem related inversely to current substance use and future intention to use. Much research that relates gateway drug use to self-esteem considers this latter construct as a unitary measure. These results from the current study corroborate those of Young, et a P with respect to school self-esteem, and confirm the utility of an areaspecific instrument. Though the school self-esteem subscale variable was not the most powerful element of the regression model, it was a statistically significant component nevertheless. The other subscales (peer and home) did not enter significantly in the regression model. Thus, health educators and other specialists working at the secondary school level should focus their attention on school self-esteem in prevention programming rather than on more generic measures of selfesteem that correlate only weakly with substance abuse. 32 The ethnicity variable showed interesting patterns of response. Respondents classifying themselves as “other” reported the most smoking activity, 36.4% of the “other” sample smoked 21 or more cigarettes per day. Of the identifiable ethnic groups, Hispanics had the highest rate (22.2%), followed by the Caucasian group (15%). The lowest smoking rate by ethnic group was among African-Americans, where 3.5% indicated they smoked at least occasionally. The more parsimonious regression model was comprised of the following variables (presented in order of strength of beta weights): ethnic group, attitude toward females who smoke, close friends’ smoking, personal use of marijuana, best friend’s smoking, personal use of alcohol, and the Hare subscale for school self-esteem. When these variables were entered into the regression model, ethnic variables became the strongest predictors of cigarette use, while close friends’ and best friend’s use, alcohol use, and marijuana use, had more modest beta weights. This observation suggests that for this sample, a strong moderating effect exists between ethnic characteristics and peer use. These ethnic variables collectively were the best demographic predictor of tobacco use. This pattern of cigarette use shows possible ethnic patterns which should be considered in future health education program development. For example, it may be necessary to develop smoking education programs culturally sensitive to Hispanic groups, to employ positive role models salient to selected cultural groups, and to develop materials written or presented in Spanish since almost one-fourth of the Hispanic students sampled here reported smoking at least occasionally. Intrepretation must be cautious, however, since the actual number of respondents in this study who identified themselves as Hispanic was small. However, data from larger studies support a need for programs to include a special ethnic or cultural sensitivity. Examination of the National Health Interview Survey data and the Hispanic Health and Nutrition Survey data by Escobedo et all4 showed that Mexican-American males, Puerto Rican-American males, and Cuban-American males -c age 18 all had smoking initiation rates higher than their non-Hispanic peers. The pattern among females, while not as pronounced, was nevertheless
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apparent. As has been suggested by other investigators,” additional factors, such as differential familial organization, unique historical/cultural milieus, reactions to societal labeling, socioeconomic status, and reading level influences on survey responses may have a mediating or interactive effect with respect to ethnicity. Another issue which may be surfacing here is that peer use of a substance, which was a good predictor of substance use in certain populations such as middle school students, may no longer be a good predictor,” because at this age, students are less interested in, or less influenced by, perceptions of their peer group’s expectations. Further research concerning peer interaction and influence may disclose more information concerning this uncertainty. References I . Penner M. Economic incentives to reduce employee smoking: A health insurance surcharge for tobacco using State of Kansas employees. A m J Health Promotion. 1989;4(1):5-11. 2 . US Dept of Health and Human Services. The Health Consequences of Smoking: Nicotine addiction. A report to the surgeon general. Washington, DC: Public Health Service, Centers for Disease Control, Center for Health Promotion and Education, Office on Smoking and Health; 1988. 3. Bonaguro EW, Bonaguro JA. Tobacco use among adolescents: Directions for research. A m J Health Promotion. 1989;4(1):3741. 4. Pierce JP, Fiore MC, Novotny TE, Hatziandreu EJ, Davis RM. Trends in cigarette smoking in the United States: Projections to the year 2OOO. JAMA. 1989;261:61-65. 5 . US Dept of Health and Human Services: Reducing the Health Consequences of Smoking: 25 years of progress. A report of the surgeon general. Rockville, Md: Office of Smoking and Health DDHS publication no CDC 89-8411; 1989. 6. Landers C, Orlandi, MA. Why do teenagers smoke and chew. Educ Horizons. 1987;65(3):133-134. 7. National Adolescent Student Health Survey: A report on the health of American youth. Kent, Ohio: American School Health Association; 1988. 8. Clarke JH. Reducing adolescent smoking: A comparison of peer-led, teacher-led, and expert interventions. J Sch Health. 1986;5 (3):102-106. 9. Krohn MD, Naughton MJ, Skinner WF, Becker SL, Lauer RM. Social disaffection, friendship patterns and adolescent cigarette use: The Muscatine Study. J Sch Health. 1986;56(3):146-150. 10. Dielman T, Leech S,Larenger A, Horvath W. Health locus of control and self-esteem as related to adolescent behavior and intentions. Adolescence. 1984; 19(76):935-950. 1 1 . Tucker L. Physical, psychological, social and lifestyle differences among adolescents classified according to cigarette intention status. J Sch Health. 1985;55(4):127-130. 12. Lauer RM, Akers RL, Massey J, Clarke WR. Evaluation of cigarette smoking among adolescents: The Muscatine Study. Prev Med. 1982;11:417428. 13. Newman IM, Ward JMW. The influence of parental attitude and behavior on early adolescent cigarette smoking. J Sch Health.
198%59(4):150-152. 14. Escobedo LO, Anda RF, Smith PF. Remington PL, Mast EE. Sociodemographic characteristics of cigarette smoking initiation in the United States. JAMA. 1990,264:1550-1555. 15. Windsor RA, Baranowski T, Clark N, Cutter G. Evaluation of Health Promotion and Education Programs. Palo Alto, Calif: Mayfield, 1984. 16. Akers RL, Massey J, Clarke W. Lauer RM. Are self-reports of adolescent deviance valid? Biochemical measures, randomized response, and the bogus pipeline in smoking behavior. Social Forces. 1983;62:234-251. 17. Bauman KE, Koch GG, Bryan ES. Validity of self-reports of adolescent cigarette smoking. Intemat J Addict. 1982;17:1131-1136. 18. Luepker RV, Pallonen UE, Murray DM, Pirie PL. Validity of telephone surveys in assessing cigarette smoking in young adults. Am J Public Health. 1989;79:202-204. 19. Slattery ML, Hunt SC, French TK, Ford HM, Williams RR. Validity of cigarette smoking habits in three epidemiologic studies in Utah. Prev Med. 1989;18:11-19. 20. Farquhar TW, Wood PD, Breitose H, Haskell WL, Meyer AJ, Maccoby N, et al. Community education for cardiovascular health. Lancet. 1977;1(8023):1192-1195. 21. Pechacek TF, Murray DM, Luepker RV, Mittlemark MB, Johnson CA, Shutz JM. Measurement of adolescent smoking behavior: Rationale and methods. J Eehav Med. 1984;11:191-203. 22. Werch CE, Gorman DR, Marty PJ, Forbess J , Brown B. Effects of the bogus-pipeline on enhancing self-reported adolescent drug use measures. J Sch Health. 1987;57(6):232-236. 23. Hare BR. Racial and socioeconomic variations in preadolescent area-specific and general self-esteem. Internal J Int Re/. 1977;1(3): 31-51. 24. McLaughlin OH: SMOG grading - a new readability formula. J Read. 1%9;12:639-646. 25. Semmer NY, Cleary PD, Dwyer JH, Fuchs R, Lippert P. Psychosocial predictors of adolescent smoking in two German cities: The Berlin-Breman Study. MMWR. 1987;36(Supple 4):3-10. 26. Schoemaker AL. Construct validity of area specific self-esteem: The Hare Self-Esteem Scale. Educ & Psycho1 Measure. 1980;40:495-501. 27. Young M. Self-esteem and sexual behavior among early adolescents. Fam Life Educ. 1989;7(4):16-19. 28. Young M, Werch CE, Bakema D: Area specific self-esteem scales and substance use among elementary and middle school children. J Sch Health. 1989;59(6):251-254. 29. Perry CL, Murray DM, Klepp K-I. Predictors of adolescent smoking and implications for prevention. MMWR. 1987;36(Suppl): 4145. 30. Cotton P. Tobacco foes attack ads that target women, minorities, teens, and the poor. JAMA. 1990;264:1505-1506. 31. Errecart MT, Walberg HJ, Ross JG, Gold RS, Fiedler JL, Kolbe LJ. Effectiveness of teenage health teaching modules. J Sch Health. 1991 ;61(1):26-30. 32. Botvin GJ. Substance abuse prevention research: Recent developments and future directions. J Sch Health. 1986;56(9):369-374. 33. Sussman S, Dent CW, Flay BR, Hansen WB, Johnson CA. Psychosocial predictors of cigarette smoking onset by White, Black, Hispanic, and Asian adolescents in southern California. MMWR. 1987;36(S~ppl): 11-16. 34. Sarvela PD, McClendon EJ. Indicators of rural youth drug use. J Youth & A d d . 1988;17(4):337-349.
Smoking and Tobacco Control - The National Cancer Institute has begun a new series of scientific monographs on smoking and tobacco control. The first monograph - Strategies to Control Tobacco Use in the United States: A blueprint for public health action in the 1990s includes topics such as the evolution of smoking control strategies and evidence of their need based on the increase in smoking prevalence and lung cancer death rates. The second monograph - Tobacco and the Clinician: Interventionsfor medical and dental practices will discuss intervention methods that have been successful and ways to expand and improve these interventions through a national program. To receive a copy of the first monograph and to be placed on the mailing list for future copies, contact: Donald R. Shopland, Smoking and Tobacco Control Coordinator, National Cancer Institute, EPN Room 241, 9ooo Rockville Pike, Bethesda, MD 20892.
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