Past 15-year trends in adolescent marijuana use: Differences by race/ethnicity and sex
Introduction
After alcohol and tobacco, marijuana has been consistently the most commonly used drug of abuse in the US. In 2012, 42.6% of Americans aged 12 and older reported lifetime marijuana use, whereas 61.9% reported lifetime cigarette use and 82.3% reported lifetime alcohol use (SAMHSA, 2014). Adolescence is the developmental period during which most people first use marijuana (Schulden et al., 2009). National data show that 23.4% of high school students report past 30-day marijuana use and that 40.1% report lifetime marijuana use in 2013 (Kann et al., 2014).
The US has undergone significant social change regarding marijuana policy in the past 15 years. Since 1996, 34 states have passed legislation removing criminal sanctions for medical use of marijuana. Twenty states have passed legislation to “decriminalize” marijuana use and possession, nine in the late 1970s and the remainder since 2001. Additionally, since 2012, statutes that effectively end sanctions for recreational marijuana use by adults (≥21 years) have been passed in four states (National Conference of State Legislatures [NCSL], 2015). There is increasingly widespread public support for loosening laws prohibiting marijuana, particularly among those younger than 30 (Palamar, 2014, The Pew Research Center, 2013, Swift, 2013).
Given the current political climate, it is important to examine patterns of adolescent marijuana use and consider how they may change if marijuana were to become legally available for recreational use. Some have argued that it will result in an increase in use among youth, because: (1) the price would likely fall dramatically – making it more affordable to young people, (2) it would be more widely available to youth (i.e., diversion from legal outlets to adolescents is likely), and (3) use will be normalized (Anderson and Rees, 2014, Friese and Grube, 2013, Pacula et al., 2014, Palamar et al., 2014). Additionally, in the absence of strong public health regulations, adolescent use could increase in response to targeted advertising and promotion efforts by corporations (D’Amico et al., 2015, Pacula et al., 2014).
Conversely, others suggest that adolescent use will remain stable or increase only marginally. A primary reason for this assertion is that existing and proposed statutes prohibit selling to minors, and selling a product illegally to minors is a risk for businesses (Anderson et al., 2014, Anderson and Rees, 2014, Pacula et al., 2014). Secondarily, the scientific evidence on changes in adolescent marijuana use following medical marijuana legislation does not suggest an increase, although additional studies with longer follow-up periods are needed to draw more definitive conclusions (Choo et al., 2014, Hasin et al., 2015). A third reason that adolescent marijuana use may increase only marginally, if at all, relates to the fact that adolescents already report that they have easy access to marijuana. National data from 2013 show that 70% of 10th graders and 81% of 12th graders say that it would be fairly easy or very easy to obtain marijuana (Johnston et al., 2014). Thus, a large portion of youth abstainers is likely doing so by choice, rather than because they lack access.
There is uncertainty about how adolescent marijuana use will change in response to policy changes, underscoring the importance of closely monitoring patterns of use. The best information about the prevalence of adolescent marijuana use comes from large, nationally representative surveillance systems. The three most widely used such datasets are the NSDUH (SAMHSA, 2014), Monitoring the Future (MTF; Johnston et al., 2014), and the National Youth Risk Behavior Survey (YRBS; Kann et al., 2014). Although direct comparisons are difficult to make given differences in the methodology of the three systems, taken together the data demonstrate that adolescent marijuana use was highest in the 1970s, declined throughout the 1980s and was lowest in 1992, and has remained somewhat stable over the past 20 years (Johnston et al., 2014, Kann et al., 2014, Lanza et al., 2015, Schulden et al., 2009, SAMHSA, 2014). MTF data show that 51% of twelfth graders reported past 12-month use of marijuana use in 1979, compared to 22% in 1992 (Johnston et al., 2014). Although adolescent marijuana use has increased since the early 1990s, the prevalence of use has not reached the peak levels seen in the 1970s (Johnston et al., 2014, Kann et al., 2014, Lanza et al., 2015, Schulden et al., 2009).
The goal of this article is to investigate trends in adolescent marijuana use since 1999. Data are from the national YRBS, which is a biennial, school-based survey that generates nationally representative estimates about health and risk behaviors, including substance use, among high school students (Kann et al., 2014). First, we examine the prevalence and trends in adolescent marijuana use for the past 15 years overall, and by race/ethnicity and sex. We examine lifetime use, past 30-day use, early use (i.e., any use before age 13), and frequent use (i.e., three or more instances of use over the past 30 days). Second, we examined the lifetime prevalence of seven additional substances (i.e., alcohol, tobacco, cocaine, ecstasy, methamphetamine, heroin, and hallucinogens) to evaluate how observed trends in adolescent marijuana use compare to those for other drugs of abuse. Third, we examine whether there were sex differences in past 30-day marijuana use within each race/ethnicity group.
We selected to use data from the YRBS rather than from other, nationally-representative and methodologically-rigorous datasets for two reasons. First, because it is administered in schools (vs. in the home), youth are less likely to underreport marijuana use (Kann et al., 2002, SAMHSA, 2012). Second, because 9th-12th graders are surveyed, grade-pooled estimates represent students in US high school students as a whole, versus just specific grades. Thus, the results we present can be used to summarize the prevalence of marijuana use in US high schools.
Section snippets
National Youth Risk Behavior Survey (YRBS)
The YRBS was initiated by the Centers for Disease Control and Prevention (CDC) in 1990 to monitor the incidence and prevalence of priority health risk behaviors among adolescents in the US (Kann et al., 2014). The CDC uses a three-stage, cluster random sampling design to obtain the YRBS samples. All 50 US states and the District of Columbia are invited to participate. The primary sampling unit (PSU) consists of counties or analogous geographic units, and the secondary sampling unit (SSU)
Trends in marijuana use among US high school students, 1999–2013
Table 1 presents national estimates of the percentage of 9th–12th graders who report marijuana use, and the first column shows the prevalence of lifetime use. Over the 15-year time period, 40.5% reported lifetime marijuana use. The annual prevalence of lifetime use decreased over time (test for linear trend: β = −0.10, p < 0.001). It was 47.2% in 1999, hit its lowest level for the time period in 2009 (36.8%), and then increased to 40.7% by 2013. The increase from 2009 to 2013 is not statistically
Discussion
The purpose of this study was to examine past 15-year trends in adolescent marijuana use among US high school students. We examined the prevalence of lifetime and past 30-day marijuana use from 1999 to 2013, overall and by sex, race/ethnicity, and year. Our rationale was that describing patterns of adolescent marijuana use will contribute to our understanding of how changes in marijuana legislation may impact future use. This is particularly important given how quickly state marijuana policies
Financial disclosure
No financial disclosures were reported by the authors of this paper.
Role of funding source
Funding for this study was provided by grants from NIH: K01DA031738 (PI: Johnson), K01AA017630 (PI: Rothman), R01AA023376 (PI: Xuan), and T32DA007292 (PI: Furr-Holden; Fairman). The study sponsor had no role in determining study design; data collection, analysis, or interpretation; writing the report; or the decision to submit the report for publication.
Contributors
Renee M Johnson drafted the entire manuscript, Ziming Xuan conducted the analysis. Brian Fairman, Tamika Gilreath, Emily Rothman, Taylor Parnham and Debra Furr-Holden assisted with writing and data interpretation.
Acknowledgement
None.
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