AJPH RESEARCH
Birth Cohorts Analysis of Adolescent Cigarette Smoking and Subsequent Marijuana and Cocaine Use Katherine M. Keyes, PhD, Ava Hamilton, BA, and Denise B. Kandel, PhD Objectives. To examine whether the drug behavior of adults from different birth cohorts is shaped by adolescent drug experiences and whether adult prevalence of marijuana and cocaine use depends on adolescent cigarette or alcohol use prevalence. Methods. We analyzed 18 birth cohorts comprising 8th, 10th, and 12th graders, sampled from 1991 to 2008, from Monitoring the Future, an annual nationally representative cross-sectional survey of high school students in the United States (n = 864 443). Results. Within cohorts, lifetime rates of 8th and 10th grade cigarette use were significantly associated with subsequent lifetime rates of marijuana and cocaine use, controlling for trends in use and social norms toward drug use. Each percent increase (or decrease) in 8th and 10th grade smoking was associated with an 8% increase (or decrease) in prevalence of later marijuana use and 14% to 23% increase (or decrease) in prevalence of later cocaine use. Relationships were consistent by gender and race/ethnicity. Conclusions. Prevalences of smoking in 8th and 10th grade and of marijuana and cocaine use in 12th grade are associated. Public health campaigns should focus on early stages of adolescence, when drug use habits are forming. (Am J Public Health. 2016;106: 1143–1149. doi:10.2105/AJPH.2016.303128) See also Galea and Vaughan, p. 973.
D
rug use often starts in adolescence with a drug that is legal for adults and proceeds to illegal drugs. Typically, the use of alcohol or tobacco precedes the use of marijuana, which in turn precedes the use of cocaine and other illicit drugs.1–7 This sequence has been observed even in recent periods, when the prevalence of marijuana use among young people has greatly increased and even surpassed that of cigarette use. Among high school seniors in 2014, 66.0% reported ever drinking alcohol, 34.4% smoking cigarettes, 44.4% using marijuana, and 4.6% using cocaine.8 Of the marijuana users, 47.2% smoked or drank alcohol before using marijuana, 37.3% started in the same grade, 11.3% started using marijuana before smoking or drinking, and 4.2% never smoked nor drank. Parallel percentages for cocaine users were 84.4%, 10.4%, 2.8%, and 2.4%, respectively. This progression has led to the notion that drugs, such as alcohol and
June 2016, Vol 106, No. 6
AJPH
tobacco, can be considered to be “gateways” to the use of other drugs.1–3,6 However, although most cocaine users have smoked cigarettes, very few smokers progress to cocaine; only 11.6% did so by 12th grade compared with 0.8% of nonsmokers. An alternate interpretation is that the use of multiple drugs reflects a common liability for drug use, which itself, rather than using a particular drug, increases the risk of using another drug.9 Generalized risks include common genetic predispositions, psychosocial factors conducive to using any drug, and environmental factors, including drug
availability, opportunities for use, and societal norms favorable to drug use.4,10–14 Both generalized risk across drugs and drug-specific risk, attributable particularly to tobacco use, have been identified.5 Although common factors may explain the use of drugs in general, specific factors may explain why young people use specific drugs and in a particular sequence. Evidence supporting a causal mechanism for the sequence between 2 drugs derives from translational research. Nicotine pretreatment in mice enhances the subsequence response to later cocaine exposure but not vice versa.15 Nicotine exerts a priming effect on cocaine through increased global histone acetylation in the striatum of the nucleus accumbens, creating an environment primed for induction of gene expression. Similarly, mice exposed to nicotine in early adolescence showed increased conditioned place preference for cocaine in adulthood through induced AFosb expression.16 The results provide a biological basis and a molecular mechanism for the sequence of drug use observed in people: one drug affects the circuitry of the brain in a manner that potentiates the effects of a subsequent drug.15,17 At the population level, if the order of drug use onset is relevant, the drug behavior of adults at different historical periods will vary as a function of the prevalence of specific drugs used in adolescence. Degenhardt et al.6 used a similar argument on
ABOUT THE AUTHORS Katherine M. Keyes and Ava Hamilton are with the Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY. Denise B. Kandel is with the College of Physicians and Surgeons, Columbia University, and the New York State Psychiatric Institute, New York. Correspondence should be sent to Denise B. Kandel, PhD, Department of Psychiatry and Mailman School of Public Health, 1051 Riverside Drive, Unit 20, New York, NY 10032 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph. org by clicking the “Reprints” link. This article was accepted February 6, 2016. doi: 10.2105/AJPH.2016.303128
Kandel et al.
Peer Reviewed
Research
1143
AJPH RESEARCH
the basis of examining the impact of variations in adolescent drug behavior across 17 countries during the same historical period. Prevalence of adolescent smoking and alcohol use predicted use of other drugs by age 29 years. We hypothesized that birth cohorts in which a higher percentage of adolescents smoked cigarettes early in adolescence would also have a higher prevalence of marijuana and cocaine use in later adolescence and early adulthood; the reverse would hold for birth cohorts with a lower prevalence of smoking in adolescence. To test the hypothesis, longitudinal data from different birth cohorts followed from adolescence to adulthood would be optimal. However, repeated cross-sectional surveys from representative national samples are a suitable alternative, because age groups in successive surveys are random subsamples of their respective birth cohorts. It is also important to control for other common causal explanations of the associations, such as social norms regarding drug use. Observed patterns may reflect changing norms about all forms of drug use in each birth cohort. Increases in negative norms in a birth cohort would produce lower rates of smoking in adolescence and lower rates of marijuana and cocaine use in adulthood. We examined sequential patterns of drug use over a short interval from early to late adolescence by taking advantage of historical variations in rates of cigarette use in early adolescence and repeated nationally representative surveys of drug use among high school students spanning 22 years. We examined the lifetime marijuana and cocaine use of 12th graders as a function of levels of smoking experienced 2 or 4 years earlier by 8th or 10th graders in 18 birth cohorts sampled from 1991 to 2008. These cohorts spanned a period of lower smoking prevalence among 8th graders (44.0%) in 1991, a period of peak prevalence (49.2%) in 1996, and a period of much lower prevalence (20.5%) in 2008. We implemented analysis by gender and race/ethnicity. African Americans appear to be less likely than are Whites to follow the sequence from tobacco to marijuana,18 although the sequence has been observed in community samples.19
1144
Research
Peer Reviewed
Kandel et al.
METHODS Data are from Monitoring the Future, an annual nationally representative crosssectional survey of US high school students.8 Approximately 45 000 8th, 10th, and 12th grade students have been sampled annually since 1991, with questionnaires collected in classrooms from approximately 420 public and private high and middle schools. A multistage random sampling procedure is implemented, with selection of primary sampling units, then 1 or more schools in each unit, with selection probability proportionate to size, then classes within each school. No more than 350 students are surveyed per school. We analyzed public use data as of 1991, except for subgroup analyses that were implemented in a restricted data file with more detailed information on race/ethnicity. The file, restricted to the 3 modal ages in each grade, includes 92.2% of the total sample. Prevalence estimates of cigarette, marijuana, and cocaine use did not differ in the 2 files (discrepancies of 0.0%–0.5%). The analytical sample included 307 330 8th graders, 277 910 10th graders, and 254 843 12th graders. The sample in some analyses is smaller because of missing data or the use of restricted data. In all our analyses, we used sample weights to provide nationally representative estimates. We standardized the age distributions of the 10th and 12th graders on 8th graders to correct for the changing age distributions within cohorts because of the increasing dropout rate in 10th (4%) and 12th (6%) grades between 1991 and 2012,20 and the gradual shift toward younger adolescents in older grades.
Measures We studied sequential cohorts on the basis of grade and survey year. The sample included 8th graders surveyed in 1991 to 2008 who belonged to the same birth cohorts as 10th graders in 1993 to 1996 and 12th graders in 1995–2012. We studied lifetime cigarette use in 8th and 10th graders. Five response categories ranged from “never smoked” to “once or twice” to “regularly now.” We measured lifetime marijuana and cocaine use in 12th grade each by a 7-category variable for number of occasions of use (0, 1–2, 3–5, 6–9, 10–19, 20– 39, ‡ 40). We dichotomized responses as
“never used” versus “used on 1 or more occasions” for all 3 drugs. Among the respondents, 51.4% were female; 62.5% were White, 13.3% African American, 12.2% Hispanic, 4.0% Asian, and 8.1% another or a mixed race/ethnicity. The mean age of the sample was 14.0 years (SD = 0.56) in 8th grade, 16.0 years (SD = 0.52) in 10th grade, and 18.0 years (SD = 0.49) in 12th grade. We created a latent dimensional variable for each cohort on the basis of 14 questions about perceived harmfulness of using cigarettes, smokeless tobacco, marijuana, alcoholic beverages (beer, wine, liquor), cocaine, and crack, and sniffing glue, gases, or sprays. We dichotomized each response (“great” vs “moderate,” “slight,” “no” risk).8,21 We combined data for all grades across all years and estimated a 1-factor model (factor loadings are shown in Table A, available as a supplement to the online version of this article at http:// www.ajph.org). Items exhibited adequate unidimensionality (eigenvalue = 8.02; comparative fit index = 0.92; Tucker-Lewis index = 0.91; root mean square error of approximation = 0.11; standardized root mean squared residual = 0.15). On the basis of the latent variable distribution across all cohorts, we generated a factor score for each respondent (total sample mean = 0; SD = 1), reflecting negative or positive attitudes regarding drug use compared with the mean for all cohorts. We included the estimated mean factor score (“mean social norm”) for each cohort in 8th grade as a control in the regressions. When aggregated at the cohort level, the overall 8th grade mean was 0.0 (SD = 0.07; minimum ―0.07 [2002], maximum 0.16 [1991]). The correlation between factor score means and smoking prevalence by cohort was 0.42 (P = .08).
Statistical Analysis We compared the percent change over time in 8th grade cigarette use with changes in marijuana and cocaine use in the corresponding 12th grade cohorts for periods of increasing (1991–1996) and decreasing (1996–2008) 8th grade smoking prevalence. We calculated the difference between the base prevalence rate of each drug and the final year of each historical period divided by the base rate to obtain a measure of relative change.
AJPH
June 2016, Vol 106, No. 6
AJPH RESEARCH
To test whether the prevalence of marijuana and cocaine use in 12th grade varied systematically with the prevalence of smoking in 8th and 10th grades, we regressed the aggregate prevalence of marijuana and cocaine use in 12th grade on the prevalence of cigarette use for the same cohorts in 8th and 10th grades. We adjusted regressions for (1) marijuana or cocaine use prevalence in earlier grades, when predicting each drug, to ensure that the associations were specific to cigarette use prevalence rather than to overall trends in marijuana or cocaine use, and (2) social norms regarding the harmfulness of drugs to control for the role of common causal factors in the associations between levels of smoking and other drugs. We interpreted the association between 8th grade smoking prevalence with later marijuana and cocaine use as being independent of the general social norms around drug use for that cohort. We stratified regressions by gender and race/ethnicity in additional analyses. To gain insights into the magnitude of changes in the prevalence of marijuana and cocaine use that could be accounted for by changes in smoking prevalence, we calculated the expected percent change in 12th grade
marijuana and cocaine use considering a 1-percentage point increase in the prevalence of 8th or 10th grade cigarette use. We multiplied the standardized parameter estimates from the multivariable linear regression by its SE to get a measure of the average change expected, considering a 1-unit increase in prevalence of smoking in 8th or 10th grade. Next, we estimated the average prevalence of marijuana and cocaine use for 12th graders across all years— marijuana (45.6%) cocaine (7.5%)—and added the 1-unit change to that estimate. Finally, we divided that estimate by the average prevalence to get a percent expected change.
RESULTS Prevalence of lifetime cigarette use among 8th graders increased from 44.5% in 1991 to 49.2% in 1996, when it peaked, and declined steadily through 2008 to 20.5% (Figure 1).
Eighth Grade Smoking and Subsequent Drug Use Figure 2 displays the relative percent changes in the lifetime prevalence of smoking
60
49.2
Ever Smoked in 8th Grade, %
50
46.1 46.4 45.2 45.3
44.0
47.3
45.7
44.1 40.5
40
36.6 31.4 28.4 27.9
30
25.9
24.6 22.1
20.5
20
10
92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08
19
19
91
0
Survey Year Source. Johnston et al.8
FIGURE 1—Prevalence of Lifetime Cigarette Use in 8th Grade: 18 Monitoring the Future Surveys, United States, 1991–2008
June 2016, Vol 106, No. 6
AJPH
in 8th grade and subsequent marijuana and cocaine use in 12th grade for the cohorts that spanned increases or decreases in overall smoking prevalence. There was a 10.5% relative increase in smoking prevalence for the 8th grade cohorts from 1991 to 1996. When in 12th grade, 4 years later, the relative prevalence of marijuana use increased by 16.8% and that of cocaine use by 44.5%. By contrast, when smoking decreased by 58.3% between 1996 and 2008 in 8th grade, the relative prevalence of marijuana use and cocaine use also decreased by 7.3% and 43.1%, respectively, in 12th grade. We estimated multivariable linear regressions to specify the cohort-level association between the prevalence of smoking experienced in 8th and 10th grade on marijuana and cocaine prevalence in 12th grade, controlling for the prevalence of marijuana or cocaine use in 8th grade and social norms regarding the harmfulness of drug use characterizing each cohort (Table 1). Lifetime cigarette use in 8th and 10th grade was significantly associated with 12th grade lifetime marijuana use (8th–12th grade: B = 1.35; 95% confidence interval [CI] = 0.52, 2.18; 10th–12th grade: B = 1.36; 95% CI = 0.61, 2.12) and lifetime cocaine use (8th–12th grade: B = 1.21; 95% CI = 0.55, 1.87; 10th–12th grade: B = 0.74; 95% CI = 0.16, 1.32). Positive coefficients indicate that increasing smoking prevalence in 8th grade is associated with increasing marijuana and cocaine use prevalence for those cohorts in later grades; negative coefficients indicate that decreasing smoking prevalence in 8th grade is associated with decreasing marijuana and cocaine use prevalence in later grades. Cohorts with higher prevalence of smoking in 8th grade and 10th grade had higher prevalence of marijuana and cocaine use in 12th grade than did cohorts with lower smoking prevalence in 8th and 10th grades. Coefficients were similar for marijuana and cocaine: there was more than half an expected percentage point increase in marijuana (1.35) and cocaine (1.21) use in 12th grade with each percentage point increase in 8th grade smoking and more than a third of an expected percentage point increase in marijuana (1.36) and cocaine (0.74) use in 12th grade with each percentage point increase in 10th grade smoking.
Kandel et al.
Peer Reviewed
Research
1145
AJPH RESEARCH
60.0 Legend
44.5%
8th grade smoking
40.0
Percent Change in Drug Use
12th grade marijuana 12th grade cocaine
20.0
16.8% 10.5%
0.0
1996–2008 1991–1996
1995–2000
2000–2012
2000–2012
1995–2000 –7.3%
–20.0
–40.0 –43.1%
–60.0
–58.3%
Birth Cohort Note. Percent change = difference between first and last year prevalence in each group divided by first year prevalence.
FIGURE 2—Relative Percent Change in Prevalence of Smoking in 8th Grade and Subsequent Marijuana and Cocaine Use in 12th Grade 5 Years Later Among Two Groups of Birth Cohorts in Periods When Smoking Prevalence Increased (1991–1996) and Then Decreased (1996–2008): United States
To obtain a substantive estimate of changes in drug use specified by the standardized parameter estimates, we estimated the expected percent change in 12th grade lifetime marijuana and cocaine use considering a 1 percentage point change in smoking prevalence in 8th and 10th grade relative to the average rates among adolescents in 12th grade across historical time. Each percentage point increase (or decrease) in smoking in 8th grade was associated with an 8% increase (or decrease) in the prevalence of lifetime marijuana use in 12th grade relative to the average prevalence of 45.6% observed across all 12th grade cohorts from 1995 to 2012 and a 14% to 23% increase (or decrease) in the prevalence of cocaine use in 12th grade, relative to the average prevalence of 7.5% across 12th grade cohorts.
Gender and Race/Ethnicity Table 2 presents the associations between 8th and 10th grade lifetime cigarette use and 12th grade lifetime marijuana and cocaine use by gender and race/ethnicity. The results are alike by gender. Higher lifetime smoking prevalence in 8th or 10th grade is associated with higher lifetime
1146
Research
Peer Reviewed
Kandel et al.
prevalence in 12th grade of marijuana (8th grade boys: B = 0.75; 95% CI = ―0.37, 1.88; girls: B = 1.17; 95% CI = 0.63, 1.71; 10th grade boys: B = 1.29; 95% CI = 0.25, 2.33; girls: B = 1.02; 95% CI = 0.53, 1.52) and cocaine (8th grade boys: B = 1.10; 95% CI = 0.19, 2.00; girls: B = 1.06; 95% CI = 0.63, 1.49; 10th grade boys: B = 0.95; 95% CI = 0.26, 1.64; girls: B = 0.50; 95% CI = 0.03, 0.98). Regarding race/ethnicity, there are significant positive relations between prevalence of 8th grade smoking and 12th grade marijuana use only for White and Hispanic adolescents (Whites: B = 0.97; 95% CI = 0.21, 1.73; Hispanics: B = 0.98; 95% CI = 0.10, 1.86). For cocaine, the associations between prevalence of 8th grade smoking and 12th grade cocaine use are significant for Whites (B = 1.10; 95% CI = 0.50, 1.70), Hispanics (B = 0.80; 95% CI = 0.18, 1.43), and others (B = 0.77; 95% CI = 0.29, 1.25).
DISCUSSION Using trend data spanning 22 years, we have documented an association between
prevalence of adolescent smoking in 8th and 10th grade and prevalence of marijuana and cocaine use for these cohorts in 12th grade, controlling for historical trends in marijuana and cocaine use prevalence and a common cause of the use of different drugs, namely social norms toward drug use in each cohort. Thus, sequences of drug use from cigarettes to marijuana and cocaine can be observed at the population level through historical variations in drug use prevalence in adolescence. As prevalence of adolescent smoking increases, so does the subsequent prevalence of marijuana and cocaine use. As prevalence of adolescent smoking decreases, so does the subsequent prevalence of marijuana and cocaine use. These trends are more pronounced for cocaine than marijuana. We estimate that each percentage point decrease in the prevalence of smoking in 8th and 10th grade is associated with an 8% decrease in prevalence of later marijuana use and a 14% to 23% decrease in prevalence of later cocaine use. These expected changes imply substantial public health benefit. On the basis of the 2010 census, there are approximately 22 million adolescents aged 15 to 19 years in the United States.22 We expect, on the basis of 2014 data from Monitoring the Future,8 that about 9.8 million (44.4%) will have tried marijuana at least once by the 12th grade and about 1 million (4.6%) will have tried cocaine. The expected decreases in prevalence of marijuana and cocaine use by 12th grade, considering a 1 percentage point decrease in smoking in 8th grade, translate into approximately 780 000 fewer adolescents who would try marijuana and 230 000 fewer who would try cocaine by 12th grade. These relationships are consistent by gender and race/ ethnicity. This cohort-level epidemiological evidence supports evidence from individual epidemiological studies in humans and animal studies that use of cigarettes influences the transition to other drugs of abuse. We did not find associations between 8th grade smoking and 12th grade marijuana and cocaine use across all racial/ethnic groups. The only significant associations were among Whites, Hispanics, and others for cocaine. The lack of associations among African Americans or Asians may be partially attributable to power (results are generally in the same direction as significant results for some groups). Rates of smoking and use of other
AJPH
June 2016, Vol 106, No. 6
AJPH RESEARCH
TABLE 1—Multivariable Linear Regressions of Lifetime Prevalence of 12th Grade Marijuana and Cocaine Use on 8th and 10th Grade Lifetime Smoking Prevalence: Monitoring the Future, United States, 1991–2008 and 1995–2012
Baseline Gradea
B (95% CI)
Expected Change in Prevalence of Marijuana or Cocaine in 12th grade,b %
Marijuana usec 8th grade smoking
1.35 (0.52, 2.18)
8
10th grade smoking
1.36 (0.61, 2.12)
8
1.21 (0.55, 1.87) 0.74 (0.16, 1.32)
23 14
Cocaine used 8th grade smoking 10th grade smoking
Note. CI = confidence interval. Samples: n = 307 330 8th grade students (1991–2008); n = 277 910 10th grade students (1993–2010); and n = 254 843 12th grade students (1995–2012). a Regression of 12th grade drug use on 8th or 10th grade smoking. b Expected change in prevalence as a function of baseline cigarette use = (average 12th grade substance use over 18 cohorts + [standardized B · SD]/average 12th grade drug use). c Adjusted for the prevalence of marijuana use and general social norm regarding drug use in 8th grade. d Adjusted for the prevalence of cocaine use and general social norm regarding drug use in 8th grade.
drugs among these racial/ethnic groups are considerably lower than are those among Whites,23,24 suggesting that there is not enough variance in drug use among these
subgroups to detect meaningful differences. However, the weaker association between cigarette and marijuana use among African Americans than Whites has been previously
noted19 as far back as the 1970s,18,25 a pattern that may reflect different cultural norms and social contexts.25 The prevalence of combustible cigarette smoking has declined over the past 15 years.26 However, this decline is compensated for by the emergence and striking increased popularity of e-cigarettes.27 Use of e-cigarettes among high school seniors tripled over 1 year from 2013 to 2014,28 when more adolescents used e-cigarettes than combustible nicotine delivery systems: 17.1% of 12th graders used e-cigarettes in the past 30 days, 13.6% smoked combustible cigarettes. In all, 23.1% had used combustible or e-cigarettes (both nicotine delivery devices) compared with 21.2% who had used marijuana.8 Other emerging tobacco products, such as hookahs, have also increased recently among US adolescents.8 Furthermore, whereas the prevalence of adolescent marijuana use decreased throughout much of the 2000s and increased from 2006 to 2013, prevalence decreased from 2013 to 2014. Among 12th graders, lifetime
TABLE 2—Multivariable Linear Regressions of Lifetime Prevalence of 12th Grade Cocaine and Marijuana Use on 8th and 10th Grade Lifetime Smoking Prevalence and Estimated Percent Change in Cocaine and Marijuana Use by Gender and Race/Ethnicity: Monitoring the Future, United States, 1991–2008 and 1995–2012 Marijuana Useb Baseline Gradea
B (95% CI)
Cocaine Usec
Expected Change in Prevalence in 12th Grade,d %
B (95% CI)
Expected Change in Prevalence in 12th Grade,d %
Boyse 8th grade
0.75 (–0.37, 1.88)
5
1.10 (0.19, 2.00)
18
10th grade
1.29 (0.25, 2.33)
8
0.95 (0.26, 1.64)
16
Girlse 8th grade
1.17 (0.63, 1.71)
8
1.06 (0.63, 1.49)
24
10th grade
1.02 (0.53, 1.52)
7
0.50 (0.03, 0.98)
12
White
0.97 (0.21, 1.73)
6
1.10 (0.50, 1.70)
24
African American Hispanic
1.02 (–0.21, 2.26) 0.98 (0.10, 1.86)
6 10
0.04 (–0.55, 0.63) 0.80 (0.18, 1.43)
2 19
Asian
–0.08 (–0.64, 0.49)
–2
0.41 (–0.06, 0.88)
12
Other
0.41 (–0.14, 0.96)
3
0.77 (0.29, 1.25)
15
Race/ethnicity,f 8th grade
Note. CI = confidence interval. a Regression of 12th grade drug use on 8th or 10th grade smoking. b Adjusted for the prevalence of marijuana use and general social norm regarding drug use in 8th grade. c Adjusted for the prevalence of cocaine use and general social norm regarding drug use in 8th grade. d Expected change in prevalence as a function of baseline cigarette use = (average 12th grade drug use over 18 cohorts + [standardized B · SD]/average 12th grade drug use). e Samples: n = 297 162 8th grade students (1991–2008); n = 272 028 10th grade students (1993–2010); and n = 244 076 12th grade students (1995–2012). Of these, 48.5% were boys and 51.5% were girls. Sample sizes differ from total sample because of missing data. f Samples: n = 294 088 8th grade students (1991–2008); n = 270 324 10th grade students (1993–2010); n = and 245 825 12th grade students (1995–2012). Of these, 63% were White, 13% African American, 12% Hispanic, 4% Asian, and 8% other. Sample sizes differ from total sample because data were analyzed in a restricted data set limited to the 3 modal ages in each grade.
June 2016, Vol 106, No. 6
AJPH
Kandel et al.
Peer Reviewed
Research
1147
AJPH RESEARCH
marijuana use decreased from 45.5% in 2013 to 44.4% in 2014. Lifetime cocaine use continued to decline. Yet, at around 4.6% prevalence, hundreds of thousands of adolescents report experimenting with cocaine. We suggest that public health campaigns to reduce the burden of drug use among adolescents focus on the early stages of adolescence, when drug use habits are forming. Prevention of cigarette smoking and use of tobacco products in adolescence should be a crucial component of a public health strategy that will affect the health of the population as it ages. On the basis of our analysis, there would be a stronger response for cocaine than marijuana use to changes in prevalence of tobacco use. The connection between tobacco use and later cocaine use is consistent with evidence from animal models that suggest that nicotine primes the induction of gene expression particular to cocaine use.15,29 Evidence from animal models and our epidemiological analysis support the gateway hypothesis, a sequential model of drug involvement. If sequential drug involvement acts in part through a neurobiological process through which nicotine primes the brain for later drug use, we should expect public health consequences from the increased popularity of e-cigarettes to include increased rates of illicit drug use. Tobacco and illicit drug use are also shaped by social and environmental factors, including peer group, availability, parental drug use, and norms regarding drug use.30–32
Strengths and Limitations The study has some limitations. We lacked individual longitudinal data; so we examined the population-level prevalence of smoking in 8th and 10th grades and the later prevalence of marijuana and cocaine use in 12th grade among students of the same birth cohorts, controlling for a potential common cause of the use of different drugs. With data for 3 time points measured in 18 birth cohorts, our effective analytic sample size is 18. However, the data on approximately 50 000 adolescents per cohort provide precise estimates for each cohort and different demographic groups, such as gender and race/ethnicity. Furthermore, we detected significant and substantial effects, indicating that we are well powered to assess these associations. In
1148
Research
Peer Reviewed
Kandel et al.
addition, because Monitoring the Future is a school-based survey and excludes dropouts, who have higher rates of drug use than do those who did not drop out, our estimates may underestimate the true effects of 8th grade smoking on subsequent marijuana and cocaine use. Finally, we could consider only 1 common cause of the association across drugs, namely social norms. Despite these limitations, this study has substantial strengths. Monitoring the Future has a broad time scale, large sample size, and national representativeness. Our analyses indicate that, controlling for general attitudes about harmfulness of drug use, cohorts with higher rates of smoking in earlier adolescence have a higher rate of marijuana and cocaine use in later adolescence. Conversely, cohorts with lower rates of smoking in adolescence subsequently have lower rates of marijuana and cocaine use. This has substantial public health relevance because chronic drug use has demonstrable and potentially long-lasting effects on neurodevelopment,33 especially during the critical period of brain development in early adolescence.34,35
Conclusions Our epidemiological data are consistent with translational research linking initial nicotine exposure to successive cocaine exposure and provide an important historical scope to understanding how school grade and birth cohort shape later drug outcomes. A focus on preventing the use of drugs, such as tobacco, early may have a cascade of benefits through emergence into adulthood. Our data should help policymakers plan and make projections regarding prevention and treatment needs. CONTRIBUTORS K. M. Keyes and D. B. Kandel drafted the article and supervised data analysis. A. Hamilton conducted data analysis and drafted sections of the article.
ACKNOWLEDGMENTS This study was supported by the National Institutes of Health (grants K01 AA021511 to K. M. K. and R01 DA001411).
HUMAN PARTICIPANT PROTECTION Approval by the institutional review board of Columbia University Medical Center was not necessary for this study because the analyses were implemented on publicly available data sets and the participants could not be identified.
REFERENCES 1. Kandel D. Stages in adolescent involvement in drug use. Science. 1975;190(4217):912–914. 2. Kandel DB. Stages and Pathways of Drug Involvement: Examining the Gateway Hypothesis. Cambridge, UK: Cambridge University Press; 2002. 3. Kandel D, Kandel E. The Gateway Hypothesis of substance abuse: developmental, biological and societal perspectives. Acta Paediatr. 2015;104(2):130–137. 4. Wagner FA, Anthony JC. Into the world of illegal drug use: exposure opportunity and other mechanisms linking the use of alcohol, tobacco, marijuana, and cocaine. Am J Epidemiol. 2002;155(10):918–925. 5. Huizink AC, Lev¨alathi E, Korhonen T, et al. Tobacco, cannabis, and other illicit drug use among Finnish adolescent twins: causal relationship or correlated liabilities? J Stud Alcohol Drugs. 2010;71(1):5–14. 6. Degenhardt L, Dierker L, Chiu WT, et al. Evaluating the drug use “gateway” theory using cross-national data: consistency and associations of the order of initiation of drug use among participants in the WHO World Mental Health Surveys. Drug Alcohol Depend. 2010;108(1–2): 84–97. 7. Fergusson DM, Boden JM, Horwood LJ. Cannabis use and other illicit drug use: testing the cannabis gateway hypothesis. Addiction. 2006;101(4):556–569. 8. Johnston LD, O’Malley PM, Miech RA, Bachman JG, Schulenberg JE. Monitoring the Future National Survey Results on Drug Use, 1975–2013. Ann Arbor, MI: University of Michigan Institute for Social Research; 2014. 9. Vanyukov MM, Tarter RE, Kirillova GP, et al. Common liability to addiction and “gateway hypothesis”: theoretical, empirical and evolutionary perspective. Drug Alcohol Depend. 2012;123(suppl 1):S3–S17. 10. Verweij KJ, Zietsch BP, Lynskey MT, et al. Genetic and environmental influences on cannabis use initiation and problematic use: a meta-analysis of twin studies. Addiction. 2010;105(3):417–430. 11. Morral AR, McCaffrey DF, Paddock SM. Reassessing the marijuana gateway effect. Addiction. 2002;97(12): 1493–1504. 12. Lessem JM, Hopfer CJ, Haberstick BC, et al. Relationship between adolescent marijuana use and young adult illicit drug use. Behav Genet. 2006;36(4):498–506. 13. Palmer RH, Young SE, Hopfer CJ, et al. Developmental epidemiology of drug use and abuse in adolescence and young adulthood: evidence of generalized risk. Drug Alcohol Depend. 2009;102(1–3):78–87. 14. Cleveland HH, Wiebe RP. Understanding the association between adolescent marijuana use and later serious drug use: gateway effect or developmental trajectory. Dev Psychopathol. 2008;20(2):615–632. 15. Levine A, Huang Y, Drisaldi B, et al. Molecular mechanism for a gateway drug: epigenetic changes initiated by nicotine prime gene expression by cocaine. Sci Transl Med. 2011;3(107):107ra109. 16. Volkow ND. Epigenetics of nicotine: another nail in the coughing. Sci Transl Med. 2011;3(107):107ps43. 17. Alajaji M, Lazenka MF, Kota D, et al. Early adolescent nicotine exposure affects later-life cocaine reward in mice. Neuropharmacology. 2016;105:308–317. 18. Yamaguchi K, Kandel DB. Parametric event sequence analysis: an application to an analysis of gender and racial/ ethnic differences in patterns of drug-use progression. J Am Stat Assoc. 1996;91(43):1388–1399.
AJPH
June 2016, Vol 106, No. 6
AJPH RESEARCH
19. Vaughn M, Wallace J, Perron B, Copeland V, Howard M. Does marijuana use serve as a gateway to cigarette use for high-risk African-American youth? Am J Drug Alcohol Abuse. 2008;34(6):782–791. 20. Institute of Education Sciences. The condition of education: status dropout rates. 2013. Available at: http://nces.ed.gov/programs/coe/indicator_coj.asp9/ 5/2014. Accessed September 5, 2014. 21. Bachman JG, Johnson LD, O’Malley PM. Explaining recent increases in students’ marijuana use: impacts of perceived risks and disapproval, 1976–1996. Am J Public Health. 1998;88(6):887–892. 22. US Census Bureau. Age and sex composition: 2010. Available at: http://www.census.gov/prod/cen2010/ briefs/c2010br-03.pdf. Accessed December 30, 2014. 23. Kandel DB, Kiros GE, Schaffran C, Hu MC. Racial/ ethnic differences in cigarette smoking initiation and progression to daily smoking: a multilevel analysis. Am J Public Health. 2004;94(1):128–135. 24. Keyes KM, Vo T, Wall MM, et al. Racial/ethnic differences in use of alcohol, tobacco, and marijuana: is there a cross-over from adolescence to adulthood? Soc Sci Med. 2015;124:132–141. 25. Golub A, Johnson BD. The misuse of the “gateway theory” in US policy on drug abuse control: a secondary analysis of the muddled deduction. Int J Drug Policy. 2002; 13(1):5–19. 26. Johnston LD, Miech RA, O’Malley PM, Bachman JG, Schulenberg JE. Use of alcohol, cigarettes, and a number of illicit drugs declines among US teens. Available at: http://www.monitoringthefuture.org// pressreleases/14drugpr_complete.pdf. Accessed June 22, 2015. 27. Gostin LO, Glasner AY. E-cigarettes, vaping, and youth. JAMA. 2014;312(6):595–596. 28. Centers for Disease Control and Prevention. Tobacco use among middle and high school students—United States, 2011–2014. MMWR Morb Mortal Wkly Rep. 2015; 64(14):381–385. 29. Kandel DB, Kandel ER. A molecular basis for nicotine as a gateway drug. N Engl J Med. 2014;371(21): 2038–2039. 30. Chilcoat HD, Anthony JC. Impact of parent monitoring on initiation of drug use through late childhood. J Am Acad Child Adolesc Psychiatry. 1996;35(1):91–100. 31. Leventhal H, Glynn K, Fleming R. Is the smoking decision an “informed choice?” Effect of smoking risk factors on smoking beliefs. JAMA. 1987;257(24): 3373–3376. 32. Gilpin EA, Pierce JP. Trends in adolescent smoking initiation in the United States: is tobacco marketing an influence? Tob Control. 1997;6(2):122–127. 33. Batalla A, Bhattacharyya S, Y¨ucel M, et al. Structural and functional imaging studies in chronic cannabis users: a systematic review of adolescent and adult findings. PLoS One. 2013;8(2):e55821. 34. Collins SL, Izenwasser S. Chronic nicotine differentially alters cocaine-induced locomotor activity in adolescent vs. adult male and female rats. Neuropharmacology. 2004;46(3):349–362. 35. Bava S, Tapert SF. Adolescent brain development and the risk for alcohol and other drug problems. Neuropsychol Rev. 2010;20(4):398–413.
June 2016, Vol 106, No. 6
AJPH
Kandel et al.
Peer Reviewed
Research
1149
Birth Cohorts Analysis of Adolescent Cigarette Smoking and Subsequent Marijuana and Cocaine Use Katherine M. Keyes, PhD, Ava Hamilton, BA, and Denise B. Kandel, PhD Objectives. To examine whether the drug behavior of adults from different birth cohorts is shaped by adolescent drug experiences and whether adult prevalence of marijuana and cocaine use depends on adolescent cigarette or alcohol use prevalence. Methods. We analyzed 18 birth cohorts comprising 8th, 10th, and 12th graders, sampled from 1991 to 2008, from Monitoring the Future, an annual nationally representative cross-sectional survey of high school students in the United States (n = 864 443). Results. Within cohorts, lifetime rates of 8th and 10th grade cigarette use were significantly associated with subsequent lifetime rates of marijuana and cocaine use, controlling for trends in use and social norms toward drug use. Each percent increase (or decrease) in 8th and 10th grade smoking was associated with an 8% increase (or decrease) in prevalence of later marijuana use and 14% to 23% increase (or decrease) in prevalence of later cocaine use. Relationships were consistent by gender and race/ethnicity. Conclusions. Prevalences of smoking in 8th and 10th grade and of marijuana and cocaine use in 12th grade are associated. Public health campaigns should focus on early stages of adolescence, when drug use habits are forming. (Am J Public Health. 2016;106: 1143–1149. doi:10.2105/AJPH.2016.303128) See also Galea and Vaughan, p. 973.
D
rug use often starts in adolescence with a drug that is legal for adults and proceeds to illegal drugs. Typically, the use of alcohol or tobacco precedes the use of marijuana, which in turn precedes the use of cocaine and other illicit drugs.1–7 This sequence has been observed even in recent periods, when the prevalence of marijuana use among young people has greatly increased and even surpassed that of cigarette use. Among high school seniors in 2014, 66.0% reported ever drinking alcohol, 34.4% smoking cigarettes, 44.4% using marijuana, and 4.6% using cocaine.8 Of the marijuana users, 47.2% smoked or drank alcohol before using marijuana, 37.3% started in the same grade, 11.3% started using marijuana before smoking or drinking, and 4.2% never smoked nor drank. Parallel percentages for cocaine users were 84.4%, 10.4%, 2.8%, and 2.4%, respectively. This progression has led to the notion that drugs, such as alcohol and
June 2016, Vol 106, No. 6
AJPH
tobacco, can be considered to be “gateways” to the use of other drugs.1–3,6 However, although most cocaine users have smoked cigarettes, very few smokers progress to cocaine; only 11.6% did so by 12th grade compared with 0.8% of nonsmokers. An alternate interpretation is that the use of multiple drugs reflects a common liability for drug use, which itself, rather than using a particular drug, increases the risk of using another drug.9 Generalized risks include common genetic predispositions, psychosocial factors conducive to using any drug, and environmental factors, including drug
availability, opportunities for use, and societal norms favorable to drug use.4,10–14 Both generalized risk across drugs and drug-specific risk, attributable particularly to tobacco use, have been identified.5 Although common factors may explain the use of drugs in general, specific factors may explain why young people use specific drugs and in a particular sequence. Evidence supporting a causal mechanism for the sequence between 2 drugs derives from translational research. Nicotine pretreatment in mice enhances the subsequence response to later cocaine exposure but not vice versa.15 Nicotine exerts a priming effect on cocaine through increased global histone acetylation in the striatum of the nucleus accumbens, creating an environment primed for induction of gene expression. Similarly, mice exposed to nicotine in early adolescence showed increased conditioned place preference for cocaine in adulthood through induced AFosb expression.16 The results provide a biological basis and a molecular mechanism for the sequence of drug use observed in people: one drug affects the circuitry of the brain in a manner that potentiates the effects of a subsequent drug.15,17 At the population level, if the order of drug use onset is relevant, the drug behavior of adults at different historical periods will vary as a function of the prevalence of specific drugs used in adolescence. Degenhardt et al.6 used a similar argument on
ABOUT THE AUTHORS Katherine M. Keyes and Ava Hamilton are with the Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY. Denise B. Kandel is with the College of Physicians and Surgeons, Columbia University, and the New York State Psychiatric Institute, New York. Correspondence should be sent to Denise B. Kandel, PhD, Department of Psychiatry and Mailman School of Public Health, 1051 Riverside Drive, Unit 20, New York, NY 10032 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph. org by clicking the “Reprints” link. This article was accepted February 6, 2016. doi: 10.2105/AJPH.2016.303128
Kandel et al.
Peer Reviewed
Research
1143
AJPH RESEARCH
the basis of examining the impact of variations in adolescent drug behavior across 17 countries during the same historical period. Prevalence of adolescent smoking and alcohol use predicted use of other drugs by age 29 years. We hypothesized that birth cohorts in which a higher percentage of adolescents smoked cigarettes early in adolescence would also have a higher prevalence of marijuana and cocaine use in later adolescence and early adulthood; the reverse would hold for birth cohorts with a lower prevalence of smoking in adolescence. To test the hypothesis, longitudinal data from different birth cohorts followed from adolescence to adulthood would be optimal. However, repeated cross-sectional surveys from representative national samples are a suitable alternative, because age groups in successive surveys are random subsamples of their respective birth cohorts. It is also important to control for other common causal explanations of the associations, such as social norms regarding drug use. Observed patterns may reflect changing norms about all forms of drug use in each birth cohort. Increases in negative norms in a birth cohort would produce lower rates of smoking in adolescence and lower rates of marijuana and cocaine use in adulthood. We examined sequential patterns of drug use over a short interval from early to late adolescence by taking advantage of historical variations in rates of cigarette use in early adolescence and repeated nationally representative surveys of drug use among high school students spanning 22 years. We examined the lifetime marijuana and cocaine use of 12th graders as a function of levels of smoking experienced 2 or 4 years earlier by 8th or 10th graders in 18 birth cohorts sampled from 1991 to 2008. These cohorts spanned a period of lower smoking prevalence among 8th graders (44.0%) in 1991, a period of peak prevalence (49.2%) in 1996, and a period of much lower prevalence (20.5%) in 2008. We implemented analysis by gender and race/ethnicity. African Americans appear to be less likely than are Whites to follow the sequence from tobacco to marijuana,18 although the sequence has been observed in community samples.19
1144
Research
Peer Reviewed
Kandel et al.
METHODS Data are from Monitoring the Future, an annual nationally representative crosssectional survey of US high school students.8 Approximately 45 000 8th, 10th, and 12th grade students have been sampled annually since 1991, with questionnaires collected in classrooms from approximately 420 public and private high and middle schools. A multistage random sampling procedure is implemented, with selection of primary sampling units, then 1 or more schools in each unit, with selection probability proportionate to size, then classes within each school. No more than 350 students are surveyed per school. We analyzed public use data as of 1991, except for subgroup analyses that were implemented in a restricted data file with more detailed information on race/ethnicity. The file, restricted to the 3 modal ages in each grade, includes 92.2% of the total sample. Prevalence estimates of cigarette, marijuana, and cocaine use did not differ in the 2 files (discrepancies of 0.0%–0.5%). The analytical sample included 307 330 8th graders, 277 910 10th graders, and 254 843 12th graders. The sample in some analyses is smaller because of missing data or the use of restricted data. In all our analyses, we used sample weights to provide nationally representative estimates. We standardized the age distributions of the 10th and 12th graders on 8th graders to correct for the changing age distributions within cohorts because of the increasing dropout rate in 10th (4%) and 12th (6%) grades between 1991 and 2012,20 and the gradual shift toward younger adolescents in older grades.
Measures We studied sequential cohorts on the basis of grade and survey year. The sample included 8th graders surveyed in 1991 to 2008 who belonged to the same birth cohorts as 10th graders in 1993 to 1996 and 12th graders in 1995–2012. We studied lifetime cigarette use in 8th and 10th graders. Five response categories ranged from “never smoked” to “once or twice” to “regularly now.” We measured lifetime marijuana and cocaine use in 12th grade each by a 7-category variable for number of occasions of use (0, 1–2, 3–5, 6–9, 10–19, 20– 39, ‡ 40). We dichotomized responses as
“never used” versus “used on 1 or more occasions” for all 3 drugs. Among the respondents, 51.4% were female; 62.5% were White, 13.3% African American, 12.2% Hispanic, 4.0% Asian, and 8.1% another or a mixed race/ethnicity. The mean age of the sample was 14.0 years (SD = 0.56) in 8th grade, 16.0 years (SD = 0.52) in 10th grade, and 18.0 years (SD = 0.49) in 12th grade. We created a latent dimensional variable for each cohort on the basis of 14 questions about perceived harmfulness of using cigarettes, smokeless tobacco, marijuana, alcoholic beverages (beer, wine, liquor), cocaine, and crack, and sniffing glue, gases, or sprays. We dichotomized each response (“great” vs “moderate,” “slight,” “no” risk).8,21 We combined data for all grades across all years and estimated a 1-factor model (factor loadings are shown in Table A, available as a supplement to the online version of this article at http:// www.ajph.org). Items exhibited adequate unidimensionality (eigenvalue = 8.02; comparative fit index = 0.92; Tucker-Lewis index = 0.91; root mean square error of approximation = 0.11; standardized root mean squared residual = 0.15). On the basis of the latent variable distribution across all cohorts, we generated a factor score for each respondent (total sample mean = 0; SD = 1), reflecting negative or positive attitudes regarding drug use compared with the mean for all cohorts. We included the estimated mean factor score (“mean social norm”) for each cohort in 8th grade as a control in the regressions. When aggregated at the cohort level, the overall 8th grade mean was 0.0 (SD = 0.07; minimum ―0.07 [2002], maximum 0.16 [1991]). The correlation between factor score means and smoking prevalence by cohort was 0.42 (P = .08).
Statistical Analysis We compared the percent change over time in 8th grade cigarette use with changes in marijuana and cocaine use in the corresponding 12th grade cohorts for periods of increasing (1991–1996) and decreasing (1996–2008) 8th grade smoking prevalence. We calculated the difference between the base prevalence rate of each drug and the final year of each historical period divided by the base rate to obtain a measure of relative change.
AJPH
June 2016, Vol 106, No. 6
AJPH RESEARCH
To test whether the prevalence of marijuana and cocaine use in 12th grade varied systematically with the prevalence of smoking in 8th and 10th grades, we regressed the aggregate prevalence of marijuana and cocaine use in 12th grade on the prevalence of cigarette use for the same cohorts in 8th and 10th grades. We adjusted regressions for (1) marijuana or cocaine use prevalence in earlier grades, when predicting each drug, to ensure that the associations were specific to cigarette use prevalence rather than to overall trends in marijuana or cocaine use, and (2) social norms regarding the harmfulness of drugs to control for the role of common causal factors in the associations between levels of smoking and other drugs. We interpreted the association between 8th grade smoking prevalence with later marijuana and cocaine use as being independent of the general social norms around drug use for that cohort. We stratified regressions by gender and race/ethnicity in additional analyses. To gain insights into the magnitude of changes in the prevalence of marijuana and cocaine use that could be accounted for by changes in smoking prevalence, we calculated the expected percent change in 12th grade
marijuana and cocaine use considering a 1-percentage point increase in the prevalence of 8th or 10th grade cigarette use. We multiplied the standardized parameter estimates from the multivariable linear regression by its SE to get a measure of the average change expected, considering a 1-unit increase in prevalence of smoking in 8th or 10th grade. Next, we estimated the average prevalence of marijuana and cocaine use for 12th graders across all years— marijuana (45.6%) cocaine (7.5%)—and added the 1-unit change to that estimate. Finally, we divided that estimate by the average prevalence to get a percent expected change.
RESULTS Prevalence of lifetime cigarette use among 8th graders increased from 44.5% in 1991 to 49.2% in 1996, when it peaked, and declined steadily through 2008 to 20.5% (Figure 1).
Eighth Grade Smoking and Subsequent Drug Use Figure 2 displays the relative percent changes in the lifetime prevalence of smoking
60
49.2
Ever Smoked in 8th Grade, %
50
46.1 46.4 45.2 45.3
44.0
47.3
45.7
44.1 40.5
40
36.6 31.4 28.4 27.9
30
25.9
24.6 22.1
20.5
20
10
92 19 93 19 94 19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 20 08
19
19
91
0
Survey Year Source. Johnston et al.8
FIGURE 1—Prevalence of Lifetime Cigarette Use in 8th Grade: 18 Monitoring the Future Surveys, United States, 1991–2008
June 2016, Vol 106, No. 6
AJPH
in 8th grade and subsequent marijuana and cocaine use in 12th grade for the cohorts that spanned increases or decreases in overall smoking prevalence. There was a 10.5% relative increase in smoking prevalence for the 8th grade cohorts from 1991 to 1996. When in 12th grade, 4 years later, the relative prevalence of marijuana use increased by 16.8% and that of cocaine use by 44.5%. By contrast, when smoking decreased by 58.3% between 1996 and 2008 in 8th grade, the relative prevalence of marijuana use and cocaine use also decreased by 7.3% and 43.1%, respectively, in 12th grade. We estimated multivariable linear regressions to specify the cohort-level association between the prevalence of smoking experienced in 8th and 10th grade on marijuana and cocaine prevalence in 12th grade, controlling for the prevalence of marijuana or cocaine use in 8th grade and social norms regarding the harmfulness of drug use characterizing each cohort (Table 1). Lifetime cigarette use in 8th and 10th grade was significantly associated with 12th grade lifetime marijuana use (8th–12th grade: B = 1.35; 95% confidence interval [CI] = 0.52, 2.18; 10th–12th grade: B = 1.36; 95% CI = 0.61, 2.12) and lifetime cocaine use (8th–12th grade: B = 1.21; 95% CI = 0.55, 1.87; 10th–12th grade: B = 0.74; 95% CI = 0.16, 1.32). Positive coefficients indicate that increasing smoking prevalence in 8th grade is associated with increasing marijuana and cocaine use prevalence for those cohorts in later grades; negative coefficients indicate that decreasing smoking prevalence in 8th grade is associated with decreasing marijuana and cocaine use prevalence in later grades. Cohorts with higher prevalence of smoking in 8th grade and 10th grade had higher prevalence of marijuana and cocaine use in 12th grade than did cohorts with lower smoking prevalence in 8th and 10th grades. Coefficients were similar for marijuana and cocaine: there was more than half an expected percentage point increase in marijuana (1.35) and cocaine (1.21) use in 12th grade with each percentage point increase in 8th grade smoking and more than a third of an expected percentage point increase in marijuana (1.36) and cocaine (0.74) use in 12th grade with each percentage point increase in 10th grade smoking.
Kandel et al.
Peer Reviewed
Research
1145
AJPH RESEARCH
60.0 Legend
44.5%
8th grade smoking
40.0
Percent Change in Drug Use
12th grade marijuana 12th grade cocaine
20.0
16.8% 10.5%
0.0
1996–2008 1991–1996
1995–2000
2000–2012
2000–2012
1995–2000 –7.3%
–20.0
–40.0 –43.1%
–60.0
–58.3%
Birth Cohort Note. Percent change = difference between first and last year prevalence in each group divided by first year prevalence.
FIGURE 2—Relative Percent Change in Prevalence of Smoking in 8th Grade and Subsequent Marijuana and Cocaine Use in 12th Grade 5 Years Later Among Two Groups of Birth Cohorts in Periods When Smoking Prevalence Increased (1991–1996) and Then Decreased (1996–2008): United States
To obtain a substantive estimate of changes in drug use specified by the standardized parameter estimates, we estimated the expected percent change in 12th grade lifetime marijuana and cocaine use considering a 1 percentage point change in smoking prevalence in 8th and 10th grade relative to the average rates among adolescents in 12th grade across historical time. Each percentage point increase (or decrease) in smoking in 8th grade was associated with an 8% increase (or decrease) in the prevalence of lifetime marijuana use in 12th grade relative to the average prevalence of 45.6% observed across all 12th grade cohorts from 1995 to 2012 and a 14% to 23% increase (or decrease) in the prevalence of cocaine use in 12th grade, relative to the average prevalence of 7.5% across 12th grade cohorts.
Gender and Race/Ethnicity Table 2 presents the associations between 8th and 10th grade lifetime cigarette use and 12th grade lifetime marijuana and cocaine use by gender and race/ethnicity. The results are alike by gender. Higher lifetime smoking prevalence in 8th or 10th grade is associated with higher lifetime
1146
Research
Peer Reviewed
Kandel et al.
prevalence in 12th grade of marijuana (8th grade boys: B = 0.75; 95% CI = ―0.37, 1.88; girls: B = 1.17; 95% CI = 0.63, 1.71; 10th grade boys: B = 1.29; 95% CI = 0.25, 2.33; girls: B = 1.02; 95% CI = 0.53, 1.52) and cocaine (8th grade boys: B = 1.10; 95% CI = 0.19, 2.00; girls: B = 1.06; 95% CI = 0.63, 1.49; 10th grade boys: B = 0.95; 95% CI = 0.26, 1.64; girls: B = 0.50; 95% CI = 0.03, 0.98). Regarding race/ethnicity, there are significant positive relations between prevalence of 8th grade smoking and 12th grade marijuana use only for White and Hispanic adolescents (Whites: B = 0.97; 95% CI = 0.21, 1.73; Hispanics: B = 0.98; 95% CI = 0.10, 1.86). For cocaine, the associations between prevalence of 8th grade smoking and 12th grade cocaine use are significant for Whites (B = 1.10; 95% CI = 0.50, 1.70), Hispanics (B = 0.80; 95% CI = 0.18, 1.43), and others (B = 0.77; 95% CI = 0.29, 1.25).
DISCUSSION Using trend data spanning 22 years, we have documented an association between
prevalence of adolescent smoking in 8th and 10th grade and prevalence of marijuana and cocaine use for these cohorts in 12th grade, controlling for historical trends in marijuana and cocaine use prevalence and a common cause of the use of different drugs, namely social norms toward drug use in each cohort. Thus, sequences of drug use from cigarettes to marijuana and cocaine can be observed at the population level through historical variations in drug use prevalence in adolescence. As prevalence of adolescent smoking increases, so does the subsequent prevalence of marijuana and cocaine use. As prevalence of adolescent smoking decreases, so does the subsequent prevalence of marijuana and cocaine use. These trends are more pronounced for cocaine than marijuana. We estimate that each percentage point decrease in the prevalence of smoking in 8th and 10th grade is associated with an 8% decrease in prevalence of later marijuana use and a 14% to 23% decrease in prevalence of later cocaine use. These expected changes imply substantial public health benefit. On the basis of the 2010 census, there are approximately 22 million adolescents aged 15 to 19 years in the United States.22 We expect, on the basis of 2014 data from Monitoring the Future,8 that about 9.8 million (44.4%) will have tried marijuana at least once by the 12th grade and about 1 million (4.6%) will have tried cocaine. The expected decreases in prevalence of marijuana and cocaine use by 12th grade, considering a 1 percentage point decrease in smoking in 8th grade, translate into approximately 780 000 fewer adolescents who would try marijuana and 230 000 fewer who would try cocaine by 12th grade. These relationships are consistent by gender and race/ ethnicity. This cohort-level epidemiological evidence supports evidence from individual epidemiological studies in humans and animal studies that use of cigarettes influences the transition to other drugs of abuse. We did not find associations between 8th grade smoking and 12th grade marijuana and cocaine use across all racial/ethnic groups. The only significant associations were among Whites, Hispanics, and others for cocaine. The lack of associations among African Americans or Asians may be partially attributable to power (results are generally in the same direction as significant results for some groups). Rates of smoking and use of other
AJPH
June 2016, Vol 106, No. 6
AJPH RESEARCH
TABLE 1—Multivariable Linear Regressions of Lifetime Prevalence of 12th Grade Marijuana and Cocaine Use on 8th and 10th Grade Lifetime Smoking Prevalence: Monitoring the Future, United States, 1991–2008 and 1995–2012
Baseline Gradea
B (95% CI)
Expected Change in Prevalence of Marijuana or Cocaine in 12th grade,b %
Marijuana usec 8th grade smoking
1.35 (0.52, 2.18)
8
10th grade smoking
1.36 (0.61, 2.12)
8
1.21 (0.55, 1.87) 0.74 (0.16, 1.32)
23 14
Cocaine used 8th grade smoking 10th grade smoking
Note. CI = confidence interval. Samples: n = 307 330 8th grade students (1991–2008); n = 277 910 10th grade students (1993–2010); and n = 254 843 12th grade students (1995–2012). a Regression of 12th grade drug use on 8th or 10th grade smoking. b Expected change in prevalence as a function of baseline cigarette use = (average 12th grade substance use over 18 cohorts + [standardized B · SD]/average 12th grade drug use). c Adjusted for the prevalence of marijuana use and general social norm regarding drug use in 8th grade. d Adjusted for the prevalence of cocaine use and general social norm regarding drug use in 8th grade.
drugs among these racial/ethnic groups are considerably lower than are those among Whites,23,24 suggesting that there is not enough variance in drug use among these
subgroups to detect meaningful differences. However, the weaker association between cigarette and marijuana use among African Americans than Whites has been previously
noted19 as far back as the 1970s,18,25 a pattern that may reflect different cultural norms and social contexts.25 The prevalence of combustible cigarette smoking has declined over the past 15 years.26 However, this decline is compensated for by the emergence and striking increased popularity of e-cigarettes.27 Use of e-cigarettes among high school seniors tripled over 1 year from 2013 to 2014,28 when more adolescents used e-cigarettes than combustible nicotine delivery systems: 17.1% of 12th graders used e-cigarettes in the past 30 days, 13.6% smoked combustible cigarettes. In all, 23.1% had used combustible or e-cigarettes (both nicotine delivery devices) compared with 21.2% who had used marijuana.8 Other emerging tobacco products, such as hookahs, have also increased recently among US adolescents.8 Furthermore, whereas the prevalence of adolescent marijuana use decreased throughout much of the 2000s and increased from 2006 to 2013, prevalence decreased from 2013 to 2014. Among 12th graders, lifetime
TABLE 2—Multivariable Linear Regressions of Lifetime Prevalence of 12th Grade Cocaine and Marijuana Use on 8th and 10th Grade Lifetime Smoking Prevalence and Estimated Percent Change in Cocaine and Marijuana Use by Gender and Race/Ethnicity: Monitoring the Future, United States, 1991–2008 and 1995–2012 Marijuana Useb Baseline Gradea
B (95% CI)
Cocaine Usec
Expected Change in Prevalence in 12th Grade,d %
B (95% CI)
Expected Change in Prevalence in 12th Grade,d %
Boyse 8th grade
0.75 (–0.37, 1.88)
5
1.10 (0.19, 2.00)
18
10th grade
1.29 (0.25, 2.33)
8
0.95 (0.26, 1.64)
16
Girlse 8th grade
1.17 (0.63, 1.71)
8
1.06 (0.63, 1.49)
24
10th grade
1.02 (0.53, 1.52)
7
0.50 (0.03, 0.98)
12
White
0.97 (0.21, 1.73)
6
1.10 (0.50, 1.70)
24
African American Hispanic
1.02 (–0.21, 2.26) 0.98 (0.10, 1.86)
6 10
0.04 (–0.55, 0.63) 0.80 (0.18, 1.43)
2 19
Asian
–0.08 (–0.64, 0.49)
–2
0.41 (–0.06, 0.88)
12
Other
0.41 (–0.14, 0.96)
3
0.77 (0.29, 1.25)
15
Race/ethnicity,f 8th grade
Note. CI = confidence interval. a Regression of 12th grade drug use on 8th or 10th grade smoking. b Adjusted for the prevalence of marijuana use and general social norm regarding drug use in 8th grade. c Adjusted for the prevalence of cocaine use and general social norm regarding drug use in 8th grade. d Expected change in prevalence as a function of baseline cigarette use = (average 12th grade drug use over 18 cohorts + [standardized B · SD]/average 12th grade drug use). e Samples: n = 297 162 8th grade students (1991–2008); n = 272 028 10th grade students (1993–2010); and n = 244 076 12th grade students (1995–2012). Of these, 48.5% were boys and 51.5% were girls. Sample sizes differ from total sample because of missing data. f Samples: n = 294 088 8th grade students (1991–2008); n = 270 324 10th grade students (1993–2010); n = and 245 825 12th grade students (1995–2012). Of these, 63% were White, 13% African American, 12% Hispanic, 4% Asian, and 8% other. Sample sizes differ from total sample because data were analyzed in a restricted data set limited to the 3 modal ages in each grade.
June 2016, Vol 106, No. 6
AJPH
Kandel et al.
Peer Reviewed
Research
1147
AJPH RESEARCH
marijuana use decreased from 45.5% in 2013 to 44.4% in 2014. Lifetime cocaine use continued to decline. Yet, at around 4.6% prevalence, hundreds of thousands of adolescents report experimenting with cocaine. We suggest that public health campaigns to reduce the burden of drug use among adolescents focus on the early stages of adolescence, when drug use habits are forming. Prevention of cigarette smoking and use of tobacco products in adolescence should be a crucial component of a public health strategy that will affect the health of the population as it ages. On the basis of our analysis, there would be a stronger response for cocaine than marijuana use to changes in prevalence of tobacco use. The connection between tobacco use and later cocaine use is consistent with evidence from animal models that suggest that nicotine primes the induction of gene expression particular to cocaine use.15,29 Evidence from animal models and our epidemiological analysis support the gateway hypothesis, a sequential model of drug involvement. If sequential drug involvement acts in part through a neurobiological process through which nicotine primes the brain for later drug use, we should expect public health consequences from the increased popularity of e-cigarettes to include increased rates of illicit drug use. Tobacco and illicit drug use are also shaped by social and environmental factors, including peer group, availability, parental drug use, and norms regarding drug use.30–32
Strengths and Limitations The study has some limitations. We lacked individual longitudinal data; so we examined the population-level prevalence of smoking in 8th and 10th grades and the later prevalence of marijuana and cocaine use in 12th grade among students of the same birth cohorts, controlling for a potential common cause of the use of different drugs. With data for 3 time points measured in 18 birth cohorts, our effective analytic sample size is 18. However, the data on approximately 50 000 adolescents per cohort provide precise estimates for each cohort and different demographic groups, such as gender and race/ethnicity. Furthermore, we detected significant and substantial effects, indicating that we are well powered to assess these associations. In
1148
Research
Peer Reviewed
Kandel et al.
addition, because Monitoring the Future is a school-based survey and excludes dropouts, who have higher rates of drug use than do those who did not drop out, our estimates may underestimate the true effects of 8th grade smoking on subsequent marijuana and cocaine use. Finally, we could consider only 1 common cause of the association across drugs, namely social norms. Despite these limitations, this study has substantial strengths. Monitoring the Future has a broad time scale, large sample size, and national representativeness. Our analyses indicate that, controlling for general attitudes about harmfulness of drug use, cohorts with higher rates of smoking in earlier adolescence have a higher rate of marijuana and cocaine use in later adolescence. Conversely, cohorts with lower rates of smoking in adolescence subsequently have lower rates of marijuana and cocaine use. This has substantial public health relevance because chronic drug use has demonstrable and potentially long-lasting effects on neurodevelopment,33 especially during the critical period of brain development in early adolescence.34,35
Conclusions Our epidemiological data are consistent with translational research linking initial nicotine exposure to successive cocaine exposure and provide an important historical scope to understanding how school grade and birth cohort shape later drug outcomes. A focus on preventing the use of drugs, such as tobacco, early may have a cascade of benefits through emergence into adulthood. Our data should help policymakers plan and make projections regarding prevention and treatment needs. CONTRIBUTORS K. M. Keyes and D. B. Kandel drafted the article and supervised data analysis. A. Hamilton conducted data analysis and drafted sections of the article.
ACKNOWLEDGMENTS This study was supported by the National Institutes of Health (grants K01 AA021511 to K. M. K. and R01 DA001411).
HUMAN PARTICIPANT PROTECTION Approval by the institutional review board of Columbia University Medical Center was not necessary for this study because the analyses were implemented on publicly available data sets and the participants could not be identified.
REFERENCES 1. Kandel D. Stages in adolescent involvement in drug use. Science. 1975;190(4217):912–914. 2. Kandel DB. Stages and Pathways of Drug Involvement: Examining the Gateway Hypothesis. Cambridge, UK: Cambridge University Press; 2002. 3. Kandel D, Kandel E. The Gateway Hypothesis of substance abuse: developmental, biological and societal perspectives. Acta Paediatr. 2015;104(2):130–137. 4. Wagner FA, Anthony JC. Into the world of illegal drug use: exposure opportunity and other mechanisms linking the use of alcohol, tobacco, marijuana, and cocaine. Am J Epidemiol. 2002;155(10):918–925. 5. Huizink AC, Lev¨alathi E, Korhonen T, et al. Tobacco, cannabis, and other illicit drug use among Finnish adolescent twins: causal relationship or correlated liabilities? J Stud Alcohol Drugs. 2010;71(1):5–14. 6. Degenhardt L, Dierker L, Chiu WT, et al. Evaluating the drug use “gateway” theory using cross-national data: consistency and associations of the order of initiation of drug use among participants in the WHO World Mental Health Surveys. Drug Alcohol Depend. 2010;108(1–2): 84–97. 7. Fergusson DM, Boden JM, Horwood LJ. Cannabis use and other illicit drug use: testing the cannabis gateway hypothesis. Addiction. 2006;101(4):556–569. 8. Johnston LD, O’Malley PM, Miech RA, Bachman JG, Schulenberg JE. Monitoring the Future National Survey Results on Drug Use, 1975–2013. Ann Arbor, MI: University of Michigan Institute for Social Research; 2014. 9. Vanyukov MM, Tarter RE, Kirillova GP, et al. Common liability to addiction and “gateway hypothesis”: theoretical, empirical and evolutionary perspective. Drug Alcohol Depend. 2012;123(suppl 1):S3–S17. 10. Verweij KJ, Zietsch BP, Lynskey MT, et al. Genetic and environmental influences on cannabis use initiation and problematic use: a meta-analysis of twin studies. Addiction. 2010;105(3):417–430. 11. Morral AR, McCaffrey DF, Paddock SM. Reassessing the marijuana gateway effect. Addiction. 2002;97(12): 1493–1504. 12. Lessem JM, Hopfer CJ, Haberstick BC, et al. Relationship between adolescent marijuana use and young adult illicit drug use. Behav Genet. 2006;36(4):498–506. 13. Palmer RH, Young SE, Hopfer CJ, et al. Developmental epidemiology of drug use and abuse in adolescence and young adulthood: evidence of generalized risk. Drug Alcohol Depend. 2009;102(1–3):78–87. 14. Cleveland HH, Wiebe RP. Understanding the association between adolescent marijuana use and later serious drug use: gateway effect or developmental trajectory. Dev Psychopathol. 2008;20(2):615–632. 15. Levine A, Huang Y, Drisaldi B, et al. Molecular mechanism for a gateway drug: epigenetic changes initiated by nicotine prime gene expression by cocaine. Sci Transl Med. 2011;3(107):107ra109. 16. Volkow ND. Epigenetics of nicotine: another nail in the coughing. Sci Transl Med. 2011;3(107):107ps43. 17. Alajaji M, Lazenka MF, Kota D, et al. Early adolescent nicotine exposure affects later-life cocaine reward in mice. Neuropharmacology. 2016;105:308–317. 18. Yamaguchi K, Kandel DB. Parametric event sequence analysis: an application to an analysis of gender and racial/ ethnic differences in patterns of drug-use progression. J Am Stat Assoc. 1996;91(43):1388–1399.
AJPH
June 2016, Vol 106, No. 6
AJPH RESEARCH
19. Vaughn M, Wallace J, Perron B, Copeland V, Howard M. Does marijuana use serve as a gateway to cigarette use for high-risk African-American youth? Am J Drug Alcohol Abuse. 2008;34(6):782–791. 20. Institute of Education Sciences. The condition of education: status dropout rates. 2013. Available at: http://nces.ed.gov/programs/coe/indicator_coj.asp9/ 5/2014. Accessed September 5, 2014. 21. Bachman JG, Johnson LD, O’Malley PM. Explaining recent increases in students’ marijuana use: impacts of perceived risks and disapproval, 1976–1996. Am J Public Health. 1998;88(6):887–892. 22. US Census Bureau. Age and sex composition: 2010. Available at: http://www.census.gov/prod/cen2010/ briefs/c2010br-03.pdf. Accessed December 30, 2014. 23. Kandel DB, Kiros GE, Schaffran C, Hu MC. Racial/ ethnic differences in cigarette smoking initiation and progression to daily smoking: a multilevel analysis. Am J Public Health. 2004;94(1):128–135. 24. Keyes KM, Vo T, Wall MM, et al. Racial/ethnic differences in use of alcohol, tobacco, and marijuana: is there a cross-over from adolescence to adulthood? Soc Sci Med. 2015;124:132–141. 25. Golub A, Johnson BD. The misuse of the “gateway theory” in US policy on drug abuse control: a secondary analysis of the muddled deduction. Int J Drug Policy. 2002; 13(1):5–19. 26. Johnston LD, Miech RA, O’Malley PM, Bachman JG, Schulenberg JE. Use of alcohol, cigarettes, and a number of illicit drugs declines among US teens. Available at: http://www.monitoringthefuture.org// pressreleases/14drugpr_complete.pdf. Accessed June 22, 2015. 27. Gostin LO, Glasner AY. E-cigarettes, vaping, and youth. JAMA. 2014;312(6):595–596. 28. Centers for Disease Control and Prevention. Tobacco use among middle and high school students—United States, 2011–2014. MMWR Morb Mortal Wkly Rep. 2015; 64(14):381–385. 29. Kandel DB, Kandel ER. A molecular basis for nicotine as a gateway drug. N Engl J Med. 2014;371(21): 2038–2039. 30. Chilcoat HD, Anthony JC. Impact of parent monitoring on initiation of drug use through late childhood. J Am Acad Child Adolesc Psychiatry. 1996;35(1):91–100. 31. Leventhal H, Glynn K, Fleming R. Is the smoking decision an “informed choice?” Effect of smoking risk factors on smoking beliefs. JAMA. 1987;257(24): 3373–3376. 32. Gilpin EA, Pierce JP. Trends in adolescent smoking initiation in the United States: is tobacco marketing an influence? Tob Control. 1997;6(2):122–127. 33. Batalla A, Bhattacharyya S, Y¨ucel M, et al. Structural and functional imaging studies in chronic cannabis users: a systematic review of adolescent and adult findings. PLoS One. 2013;8(2):e55821. 34. Collins SL, Izenwasser S. Chronic nicotine differentially alters cocaine-induced locomotor activity in adolescent vs. adult male and female rats. Neuropharmacology. 2004;46(3):349–362. 35. Bava S, Tapert SF. Adolescent brain development and the risk for alcohol and other drug problems. Neuropsychol Rev. 2010;20(4):398–413.
June 2016, Vol 106, No. 6
AJPH
Kandel et al.
Peer Reviewed
Research
1149
