Abstract
Purpose:
Most studies linking prescription and illicit stimulant use measure nonmedical prescription stimulant use (NMPSU) as a dichotomous lifetime indicator. This study examined the extent to which frequency and recency of NMPSU during adolescence were associated with illicit cocaine use in young adulthood.
Methods:
Nationally representative cohorts of US 12th-graders (N = 66,082) were surveyed in the Monitoring the Future Panel study (baseline age 18, years 1976–2020; follow-up ages 19–20, years 1977–2021). Logistic regression was used to examine associations between frequency and recency of NMPSU at baseline and incident cocaine use in young adulthood.
Results:
At follow-up, 4.2 % reported past-year incident cocaine use. The odds of cocaine use increased with more frequent NMPSU in adolescence. Relative to adolescents reporting no lifetime NMPSU, the adjusted odds of incident cocaine use in young adulthood were 1.31 times greater among those reporting experimental NMPSU (1–2 times, 95 % CI=1.11–1.54), 1.63 times greater among those reporting occasional NMPSU (3–9 times, 95 % CI=1.39–1.92), and two times greater among those reporting regular NMPSU (≥10 times, AOR=2.03, 95 % CI=1.73–2.39). A similar trend was observed for recency of NMPSU; relative to adolescents with no lifetime NMPSU, the adjusted odds of incident cocaine use in young adulthood were greater among those reporting past-month NMPSU (AOR=2.11, 95 % CI=1.85–2.42) and past-year-without-past-month NMPSU (AOR=1.70, 95 % CI=1.44–2.01).
Conclusion:
NMPSU in adolescence was associated with increased odds of cocaine use in young adulthood, and the degree of risk varied by frequency and recency of NMPSU.
Keywords: Epidemiology, Stimulant, Cocaine, Adolescents, Young adults
1. Introduction
Prescription stimulants and cocaine are among the most commonly nonmedically used controlled substances in US youth (Miech et al., 2024; Patrick et al., 2024; Substance Abuse and Mental Health Services Administration [SAMHSA], 2024). In 2023, nearly one-in-20 US 12th graders reported lifetime nonmedical prescription stimulant use (NMPSU, i.e., use without a prescription or other than prescribed) (Miech et al., 2024). The nonmedical use of prescription stimulants has outpaced opioids and benzodiazepines, and is now the most prevalent type of nonmedical prescription drug use among US youth (Miech et al., 2024; Patrick et al., 2024; SAMHSA, 2024).
Cocaine use is more prevalent among young adults compared to other age groups, with 3.1 % of young adults reporting past-year cocaine use in 2023 (SAMHSA, 2024). Recent years have seen a rise in illicit stimulant-involved overdose deaths, including among adolescents and young adults (Brinzo and Martins, 2024; Hoots et al., 2020; Tanz, 2022). These trends have raised concerns about potential associations between NMPSU and the use of illicit stimulants like cocaine.
Indeed, NMPSU has been associated with cocaine use (Arria et al., 2008; Arria and DuPont, 2010; McCabe et al., 2023a; McCabe et al., 2024a; McCabe et al., 2024b; Pickens et al., 2023). However, most studies linking prescription and illicit stimulants have examined NMPSU as a dichotomous (i.e., ever versus never) variable. There is considerable heterogeneity in patterns of NMPSU, and people who have engaged in NMPSU experimentally may differ from those with occasional or more regular NMPSU in their risk profiles (McCabe and Teter, 2007). An understanding of NMPSU that includes frequency and recency may be useful for identifying and intervening with youth at risk for transitioning to cocaine use. Such efforts are urgent given the unpredictability of the illicit drug supply, which places people who use cocaine at high risk for accidental overdose (Wagner et al., 2023).
This study is among the first to examine longitudinal associations between frequency and recency of NMPSU during adolescence and cocaine use in young adulthood. Findings highlight potential targets for interventions to prevent cocaine use and stimulant-involved overdose fatalities.
2. Methods
Two waves of longitudinal data were collected from nationally representative cohorts of US 12th graders followed prospectively into young adulthood in the Monitoring the Future (MTF) Panel study. Further detail about MTF Panel methodology is available elsewhere (Patrick et al., 2024). The baseline sample included 108,487 adolescents (modal age 18, baseline years 1976–2020), a random selection of whom were invited to complete a follow-up survey at 19 or 20 years of age (N = 66,082, follow-up years 1977–2021, retention rate 60.9 %). The University of Michigan IRB exempted this secondary data analysis from further oversight.
2.1. Measures
At baseline, participants were given a description of prescription stimulants, including recognizable brand and generic names, and asked on how many occasions they had used prescription stimulants nonmedically (i.e., “on your own, without a doctor telling you to take them”) (a) in their lifetime, (b) during the past 12 months, and (c) during the past 30 days. For each period, response options were provided on a 7-point scale ranging from no occasions to 40 or more occasions. Lifetime frequency of NMPSU was categorized as no lifetime use, 1–2 times (i.e., experimental), 3–9 times (i.e., occasional), or 10 or more times (i. e., regular). Most recent NMPSU was categorized as no lifetime NMPSU, prior-to-past-year NMPSU only, past-year without past-month NMPSU, and past-month NMPSU.
At follow-up (ages 19–20), participants reported the number of occasions they used cocaine and crack cocaine during the past 12 months. These data were combined and dichotomized to indicate any past-year cocaine use. A sub-analysis examined frequency of past-year cocaine use at follow-up, categorized as no past-year use, 1–2 times, 3–9 times, and 10 or more times in the past year.
Analyses controlled for the following sociodemographic and substance use variables previously associated with NMPSU and cocaine use, coded in ways consistent with prior work (e.g., McCabe et al., 2023b; Palamar et al., 2024; Young et al., 2012): sex (male, female), racial-ethnic identity (non-Hispanic White, non-Hispanic Black, Hispanic/Latinx, other race or ethnicity), parental education (<college degree, ≥college degree), geographical region (Northeast, Midwest, South, West); urbanicity (urban, suburban, rural); cohort year (1976–1989, 1990–1999, 2000–2009, 2010–2020); intention to graduate from a four-year college (will definitely/probably complete a four-year degree, other plans); cannabis use (any lifetime); other illicit drug use (any lifetime); cigarette smoking (any past-30-days); and binge drinking (any past-two-weeks).
2.2. Statistical analysis
Analyses were conducted in Stata 18.0. Cases with missing data (n ranged 9260–9287 across models, 14.1 % of the analytic sample, Tables S1–2) were removed using listwise deletion. Models were assessed for multicollinearity, with no issues detected (Table S3). Analyses were weighted for sampling and attrition (Patrick et al., 2022). Descriptive statistics were calculated for all study variables. Logistic regression was used to examine associations between lifetime frequency and recency of NMPSU at baseline and prevalence and incidence of cocaine use in young adulthood. Models examining incident cocaine use excluded participants reporting lifetime cocaine use at baseline (n = 9181). Unadjusted and adjusted models were assessed, with odds ratios (ORs), adjusted odds ratios (AORs), and 95 % confidence intervals (CIs) reported. Sensitivity analyses used multinomial logistic regression models to examine past-year frequency of cocaine use at follow-up. To assess for changes over time, sub-analyses examined interaction effects between cohort year and lifetime frequency and recency of NMPSU at baseline, as well as models stratified by cohort year.
3. Results
Sample characteristics are presented in Table 1. At baseline, 25.6 % reported lifetime NMPSU: 7.2 % experimental, 7.7 % occasional, and 10.7 % regular. Many of those with lifetime NMPSU reported recent use, with 11.8 % of the overall sample reporting past-month NMPSU, 7.6 % reporting past-year without past-month use, and 6.3 % reporting prior-to-past-year NMPSU only.
Table 1.
Baseline characteristics of nationally representative sample of US 12th grade students from the Monitoring the Future Study (N = 108,487, 1976 – 2020).
| Characteristic | Unweighted n |
Unweighted % |
|---|---|---|
| Lifetime frequency of NMPSU | ||
| None | 79,324 | 74.4 |
| 1–2 times | 7724 | 7.2 |
| 3–9 times | 8187 | 7.7 |
| 10 + times | 11,375 | 10.7 |
| Recency of NMPSU | ||
| None | 79,390 | 74.4 |
| Prior-to-past-year NMPSU only | 6734 | 6.3 |
| Past-year without past-month NMPSU | 8068 | 7.6 |
| Past-month NMPSU | 12,556 | 11.8 |
| Cocaine use (lifetime, any) | 15,793 | 14.8 |
| Sex | ||
| Male | 52,523 | 48.7 |
| Female | 55,332 | 51.3 |
| Race and ethnicity | ||
| Non-Hispanic White | 74,857 | 69.0 |
| Non-Hispanic Black | 11,653 | 10.7 |
| Hispanic | 10,833 | 10.0 |
| Other race or ethnicity | 11,144 | 10.3 |
| Parental education | ||
| Less than college degree | 56,440 | 54.1 |
| College degree or higher | 47,834 | 45.9 |
| Geographic region | ||
| Northeast | 21,837 | 20.1 |
| Midwest | 28,631 | 26.4 |
| South | 37,753 | 34.8 |
| West | 20,266 | 18.7 |
| Urbanicity | ||
| Urban | 30,653 | 28.3 |
| Suburban | 50,501 | 46.6 |
| Rural | 27,333 | 25.2 |
| Cohort year | ||
| 1976 – 1989 | 33,975 | 31.3 |
| 1990 – 1999 | 24,617 | 22.7 |
| 2000 – 2009 | 24,517 | 22.6 |
| 2010 – 2020 | 25,378 | 23.4 |
| Intention to graduate from college | ||
| Will complete a 4-year college degree | 74,306 | 72.6 |
| Will not complete a 4-year college degree | 28,076 | 27.4 |
| Cannabis use (lifetime, any) | 57,647 | 54.4 |
| Other illicit drug use (lifetime, any) | 24,980 | 23.2 |
| Nonmedical use of other prescription drugs (lifetime, any) | 27,967 | 26.1 |
| Cigarette smoking (past 30 days) | 33,544 | 31.4 |
| Binge drinking (past 2 weeks) | 36,310 | 35.4 |
At follow-up, 4.2 % reported past-year incident cocaine use. As shown in Fig. 1, the incidence of cocaine use in young adulthood increased with frequency and recency of NMPSU in adolescence. Of those reporting no lifetime NMPSU at baseline, 3.0 % reported past-year cocaine use at follow-up, compared to 8.9 % of those reporting experimental NMPSU at baseline, 13.9 % of those reporting occasional NMPSU at baseline, and 18.7 % of those reporting more regular NMPSU at baseline. Similarly, the incidence of past-year cocaine use at follow-up was 7.8 % among those reporting prior-to-past-year NMPSU at baseline, 14.2 % among those reporting past-year without past-month NMPSU at baseline, and 18.6 % among those reporting past-month NMPSU at baseline.
Fig. 1.
Odds of Past-Year (PY) Incident Cocaine Use in Young Adulthood as a Function of Frequency and Recency of Nonmedical Prescription Stimulant Use (NMPSU) in Adolescence.
Any frequency of NMPSU in adolescence was associated with significantly greater odds of past-year incident cocaine use in young adulthood, and the odds of cocaine use increased with frequency of NMPSU in a pattern resembling a linear dose-response relationship. Compared to those reporting no lifetime NMPSU at baseline, the adjusted odds of past-year incident cocaine use at follow-up were 1.31 times greater among those reporting experimental NMPSU (95 % CI=1.11–1.54), 1.63 times greater among those reporting occasional NMPSU (95 % CI=1.39–1.92), and 2.03 times greater among those reporting more regular NMPSU (95 % CI=1.73–2.39).
Regarding recency of NMPSU at baseline, compared to those reporting no lifetime NMPSU, those reporting past-month (AOR=2.11, 95 % CI=1.85–2.42) and past-year without past-month (AOR=1.70, 95 % CI=1.44–2.01) NMPSU had significantly greater adjusted odds of past-year incident cocaine use in young adulthood. No significant difference was detected between adolescents reporting no lifetime NMPSU and those reporting prior-to-past-year NMPSU only in their adjusted odds of past-year incident cocaine use in young adulthood. The associations between frequency and recency of NMPSU at baseline and prevalence of cocaine use in young adulthood were similar (Table S4).
Several baseline sociodemographic and substance use variables were significantly associated with past-year cocaine use at follow-up. Notably, any lifetime cannabis use at baseline was associated with a more than six-fold increase in the odds of cocaine use in young adulthood (Tables S5–S6). Complete results including all control variables are available in the supplementary materials.
In the multinomial logistic regression models predicting frequency of cocaine use (Table S7), regular and recent NMPSU in adolescence were robust predictors of frequent cocaine use in young adulthood. For example, compared to those reporting no lifetime NMPSU at baseline, those reporting 10 or more occasions of NMPSU (AOR=3.44, 95 % CI=2.83–4.19) and those reporting past-month NMPSU (AOR=3.42, 95 % CI=2.84–4.11) were more than three times more likely to report regular cocaine use than no cocaine use in young adulthood. Models testing the interaction effects between cohort year and lifetime frequency and recency of NMPSU (Tables S8–S9) and stratified by cohort year (Tables S10–S11) indicate that results were largely consistent over time.
4. Discussion
Consistent with prior research linking NMPSU with later cocaine use (Arria et al., 2008; Arria and DuPont, 2010; McCabe et al., 2023a; McCabe et al., 2024a; McCabe et al., 2024b; Pickens et al., 2023), in this nationally representative sample of US youth, any frequency of NMPSU in adolescence was associated with increased odds of incident cocaine use in young adulthood. Results held across cohorts, despite shifts in adolescent NMPSU and cocaine use over time (Figure S1). However, the strength of the association varied by the frequency and recency of NMPSU. Dichotomous measures of lifetime NMPSU fail to capture this nuance that may guide tailored interventions. For example, while experimental NMPSU may indicate a need for prevention messaging, more regular NMPSU may warrant close monitoring for cocaine use. Similarly, adolescents reporting NMPSU prior to the past year only may benefit from positive reinforcement for their period of abstinence, whereas past-year NMPSU signals the need for more intensive oversight, assessment, and intervention. Further research is needed to clarify potential implications of these findings for clinical care. Importantly, however, results indicate that any frequency of NMPSU in adolescence signals a need for further assessment, continued monitoring, and linkage to adjunct services.
Multiple theories have been proposed to explain the transition from within-class prescription to illicit drug use. Some argue a priming effect is at play, given the neurobiological similarities between methylphenidate and cocaine (Volkow and Swanson, 2008). However, in this study, cannabis use in adolescence was more strongly associated with cocaine use in young adulthood than even the most recent and regular NMPSU (Tables S5–S6), potentially indicating a common liability mechanism (Vanyukov et al., 2012). Still, cannabis use is far more prevalent among adolescents than NMPSU (29.0 % versus 2.1 % of 12th graders report past-year use, respectively), and the prevalence of cannabis use remains much higher than cocaine use among young adults (Patrick et al., 2024). In this study, NMPSU remained significantly associated with cocaine use after adjusting for cannabis use and other substance use, suggesting measures of NMPSU frequency and recency provide useful information about an adolescent’s risk for future cocaine use above and beyond that of other substance use behaviors. However, further research is needed to identify the item(s) that best predict cocaine use, while considering sensitivity and specificity.
Certain limitations should be noted. Data may be limited by social desirability and recall bias. MTF’s school-based design excludes youth with higher (e.g., truant) and lower (e.g., homeschooled) prevalence of NMPSU and cocaine use. Although attrition weighting was used, differential attrition may have introduced bias. Analyses did not account for the medical use of prescription stimulants, comorbid psychiatric diagnoses, or ADHD symptoms. Future research should longitudinally examine NMPSU frequency and recency prior to and following stimulant therapy initiation and/or discontinuation, and how associations between NMPSU and cocaine use may vary by prescription stimulant formulation. Future research should also explore associations between frequency and recency of other drug use (e.g., cannabis) in adolescence and cocaine use in young adulthood.
In conclusion, the likelihood of incident cocaine use in young adulthood increased with frequency and recency of NMPSU in adolescence. Findings highlight specific time periods and frequency levels for consideration in future research and practice. Further research, including replication of this study in healthcare settings, is needed to develop brief screening protocols to assess NMPSU and thereby prevent cocaine use and related harms.
Supplementary Material
Acknowledgements
The authors would like to thank Qianyu Dang, PhD, MS; Caroline J. Huang, PhD; Jana McAninch, MD, MPH, MS; Rose Radin, PhD, MPH; Camille Smith, PharmD; Martine Solages, MD; and Zimri Yaseen, MD of the FDA for their helpful insights and feedback throughout the development and progression of this study.
Funding
This study was supported by research award 75F40121C00148 from the US Food and Drug Administration (FDA) of the US Department of Health and Human Services (HHS) and research awards R01DA001411, R01DA016575, R01DA031160, R01DA043691, UH3DA050173, and UH3DA050252 from the National Institute on Drug Abuse (NIDA) and the National Institutes of Health (NIH). The funders had no role in the study design or the analysis or interpretation of the data. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of, nor an endorsement by, the FDA/HHS, NIDA, NIH, or the US Government.
Declaration of Competing Interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Sean Esteban McCabe reports financial support was provided by US Food and Drug Administration. Sean Esteban McCabe reports financial support was provided by National Institutes of Health. Megan Patrick reports financial support was provided by National Institutes of Health. Ty Schepis reports financial support was provided by National Institutes of Health. Tim Wilens reports financial support was provided by National Institutes of Health. Tim Wilens reports a relationship with 3D Therapy that includes: funding grants. Tim Wilens reports a relationship with Major League Baseball that includes: consulting or advisory. Tim Wilens reports a relationship with Bay Cove Human Services Inc that includes: consulting or advisory. Tim Wilens reports a relationship with Gavin Foundation that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Footnotes
CRediT authorship contribution statement
Timothy E. Wilens: Writing – review & editing. Sean Esteban McCabe: Writing – review & editing, Funding acquisition, Methodology, Conceptualization. Emily Pasman: Methodology, Writing – original draft, Conceptualization. Ty S. Schepis: Writing – review & editing. Vita V. McCabe: Writing – review & editing. Philip T. Veliz: Writing – review & editing, Data curation, Formal analysis. Megan E. Patrick: Writing – review & editing.
Appendix A. Supporting information
Supplementary data associated with this article can be found in the online version at doi:10.1016/j.drugalcdep.2025.112760.
Data availability
This study contains the results of secondary analysis of restricted panel data from the US Monitoring the Future (MTF) surveys. The authors followed university and MTF protocol regarding access to and analysis of the data for this study. More information is available here: https://www.icpsr.umich.edu/web/NAHDAP/series/2520.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
This study contains the results of secondary analysis of restricted panel data from the US Monitoring the Future (MTF) surveys. The authors followed university and MTF protocol regarding access to and analysis of the data for this study. More information is available here: https://www.icpsr.umich.edu/web/NAHDAP/series/2520.