Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2023 Dec 1.
Published in final edited form as: J Subst Abuse Treat. 2022 Sep 30;143:108894. doi: 10.1016/j.jsat.2022.108894

Associations between prescription and illicit stimulant and opioid use in the United States, 2015–2020

Riley D Shearer a,b,*, Abenaa Jones c, Benjamin A Howell d,e, Joel E Segel f,g, Tyler N A Winkelman b,h
PMCID: PMC9706463  NIHMSID: NIHMS1847479  PMID: 36206585

Abstract

Introduction:

Overdose deaths involving opioids and stimulants continue to reach unprecedented levels in the United States. Although significant attention has been paid to the relationship between prescription and illicit opioid use, little work has focused on the association between prescription and illicit stimulant use. Thus, this study explores characteristics of those who use or misuse prescription stimulants and/or opioids and associations with use of cocaine, methamphetamine, and heroin.

Methods:

We used 2015–2020 data from the National Survey on Drug Use and Health. Using adjusted multivariable logistic regression, we estimated the associations between past year prescription stimulant or prescription opioid prescribed use and misuse; various demographic characteristics; and past-year cocaine, methamphetamine, or heroin use.

Results:

From 2015 to 2020, 4.9 and 9.8 million US adults annually reported misusing prescription stimulants and opioids, respectively. Individuals who misused prescription stimulants were more likely to be ages 18–25 (45.8 %; 95 % CI: 44.0–47.5) than individuals who misused prescription opioids (21.7 %; 95 % CI: 20.7–22.7). We observed higher rates of cocaine use among individuals reporting prescription stimulant misuse (12.0 %; 95 % CI: 11.0–12.9) compared to those reporting prescription opioid misuse (5.7 %; 95 % CI: 5.1–6.3, p < 0.001). Heroin use was more common among individuals with prescription opioid misuse (2.1 %; 95 % CI: 1.7–2.2) than prescription stimulant misuse (0.6 %; 95 % CI: 0.4–0.7, p < 0.001). However, rates of methamphetamine use among individuals with prescription stimulant misuse (2.4 %; 95 % CI: 1.9–3.0) did not differ from individuals with prescription opioid misuse (2.1 %; 95 % CI: 1.7–2.5, p = 0.67).

Conclusions:

Prescription stimulant misuse, compared to prescription opioid misuse, was associated with higher levels of cocaine use but not methamphetamine use. Treatment providers should consider screening for other substance use disorders among people who report prescription stimulant use or misuse. Additional research should seek to understand the mechanism underlying the different associations between prescription stimulant misuse and cocaine or methamphetamine use.

Keywords: Stimulants, Prescription misuse, Cocaine, Methamphetamine

1. Introduction

Between 2010 and 2021, a 5-fold increase has occurred in cocaine involved overdose deaths and a 18-fold increase in psychostimulant (methamphetamine) involved overdose deaths (Hedegaard et al., 2020). In 2021 alone, an estimated 107,622 drug overdose deaths occurred. Synthetic opioids (fentanyl), methamphetamine, and cocaine were involved in approximately 71,000, 33,000, and 25,000 overdose deaths, respectively (National Center for Health Statistics, 2022). The increase in stimulant overdose deaths likely reflects increasing stimulant use and concurrent use with synthetic opioids (Ciccarone, 2021). Fatal overdoses are not the only adverse outcome of stimulant use. Cocaine and methamphetamine use are also associated with increased morbidity, including high rates of infectious diseases and disability (Butler et al., 2017; Shearer et al., 2020). Although new and promising pharmacologic treatments are in development for stimulant use disorder, particularly for methamphetamine use disorder (Trivedi et al., 2021), prevention of methamphetamine and cocaine use initiation remains a critical component of reducing stimulant-related morbidity and mortality (Ballester et al., 2017; Kampman, 2019). Despite the known adverse health consequences, the underlying factors associated with cocaine and methamphetamine use remain unclear.

Consistent evidence has found that heroin use is often preceded by prescription opioid misuse (Cicero et al., 2014; Lankenau, Teti, et al., 2012; Peavy et al., 2012; Pollini et al., 2011). Furthermore, prescription opioid misuse is associated with higher rates of heroin use than prescription opioid use or no use (Jones, 2013). Research has investigated comparatively less so the associations between prescription stimulant misuse and cocaine or methamphetamine use. Although parallel increases in both self-reported misuse and emergency department visits involving prescription stimulants and methamphetamine have occurred, to what extent, if any, the trends are related is unclear (Chen et al., 2016; Vivolo-Kantor et al., 2020). A retrospective study of adolescents found that illicit substance use was often preceded by misuse of prescription substances with similar psychotropic effects (Lankenau, Schrager, et al., 2012). Furthermore, a recent study of HIV-vulnerable sexual and gender minorities who have sex with men found that individuals who misused prescription stimulants had a 2.5-fold increased risk of using methamphetamine 12 months later (Westmoreland et al., 2021). However, these past studies are small, geographically limited, and focused on specific populations. The associations between prescription stimulant use and cocaine or methamphetamine use, among the broader US population, have not been well characterized in the literature.

Studies from the extant literature have broadly grouped illicit substances, with different psychotropic effects, into one category and demonstrated high rates of substance use among individuals who report prescription stimulant misuse (Chen et al., 2015; Compton et al., 2018; Wang et al., 2015). Mustaquim and colleagues documented high rates of prescription stimulant misuse among individuals who use cocaine (Mustaquim et al., 2021). However, we know little about possible differences in cocaine, methamphetamine, and heroin use among individuals who use or misuse prescription stimulants or prescription opioids. Research describing these complex relationships is needed for researchers, clinicians, and public health officials to develop prevention programs, target screening, identify treatment needs, and expand harm reduction programs.

In this study, we assessed sociodemographic and health factors among individuals with varying prescription stimulant and opioid use patterns (including no use, use, and misuse). We compared characteristics of misuse (e.g., frequency and duration) between individuals with prescription stimulant and opioid misuse. We then compared associations between prescription stimulant or opioid use/misuse and use of three substances: cocaine, methamphetamine, and heroin. We hypothesized that: 1) rates of past year cocaine, methamphetamine, and heroin use would be highest among individuals with prescription misuse compared to prescribed use or no use; and 2) prescription misuse would be associated with higher rates of substance use with similar psychotropic effects, specifically misuse of prescription stimulants would be associated with higher rates of cocaine and methamphetamine use than prescription opioid misuse, while prescription opioid misuse would be associated with higher rates of heroin use than prescription stimulant misuse.

2. Materials and methods

2.1. Data source

We used data from the National Survey on Drug Use and Health (NSDUH), a nationally representative survey of the US civilian population aged 12 and older (Substance Abuse and Mental Health Services Administration, 2020). NSDUH provides information on the use of prescription and other substances in addition to demographic information and measures of mental and physical health. To better capture rates of prescription drug misuse, the questionnaire underwent a partial redesign in 2015. For this analysis, we pooled data from 2015 through 2020 for all adult respondents aged 18 and older.

2.2. Prescription opioid and stimulant measures

To compare characteristics of people who report prescription stimulant versus opioid use, we generated a unique categorical variable for each prescription substance indicating varying levels of reported use. For both prescription stimulants and opioids, we categorized respondents separately into three mutually exclusive groups based on past year use including: 1) no use, 2) use without misuse (referred to as prescribed use), and 3) misuse. Misuse, often referred to as nonmedical use, is defined by NSDUH as any use in a way not directed by a doctor.

2.3. Substance use outcomes

The outcomes of interest were cocaine, methamphetamine, and heroin use. For each substance, we generated a unique binary variable (past-year use vs. no past-year use) based on whether an individual reported use in the past 12 months.

2.4. Sociodemographic, health, and prescription misuse characteristics

We examined several characteristics among people who reported prescription stimulant and opioid use and misuse. We described self-reported sociodemographic variables including gender, race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, and other), age, income (defined as <100 %, 100–200 %, and >200 % of the Federal Poverty Line), health insurance status, educational attainment, rural residence, housing instability, and recent criminal legal involvement (CLI). We categorized individuals as having private, Medicaid, other health insurance (e.g. Medicare or military health care), or as uninsured. Rural residence was defined as a nonmetro county using 2013 rural/urban continuum codes 4–9. Although NSDUH does not contain an explicit question on housing stability, we defined a binary variable as moving three or more times in the past year, consistent with previous literature (Frederick et al., 2014). We generated a binary variable for recent CLI, which included reports of any arrests, probation, or parole in the past year.

Given high rates of co-occurring substance misuse and physical and/or behavioral health disorders, we included indicators of severe mental illness (SMI) and self-reported health. For the NSDUH, the Substance Abuse and Mental Health Services Administration uses a validated predictive model for SMI that accounts for measures from the Kessler Psychological Distress Scale (K6) and World Health Organization Disability Assessment Scale (Kessler et al., 2003; Substance Abuse and Mental Health Services Administration, 2019). Respondents also rated their overall health as excellent, very good, good, fair, or poor. We generated a binary variable indicating individuals who reported fair or poor health.

Among those who reported prescription stimulant or opioid misuse, we further characterized the patterns of prescription misuse. To contextualize our findings with previous research describing high rates of prescription stimulant and opioid diversion as well as co-use with other substances, we examined binary variables for whether a respondent did not have a prescription or if they co-ingested alcohol (Compton et al., 2018; McCabe et al., 2015). We also examined whether an individual misused a substance by consuming more of it than prescribed. We created three separate binary indicators for whether an individual reported taking the prescription in greater amounts, more frequently, or for longer than prescribed. Characteristics of misuse were not mutually exclusive.

2.5. Statistical analysis

First, we estimated the weighted prevalence of prescribed use and misuse of prescription stimulants and opioids using the sample weights provided by NSDUH. We cross tabulated these two groups to observe the overlap. We then compared the sociodemographic characteristics between each category of prescription stimulant and opioid use. Among those who reported either past-year prescription stimulant or opioid misuse, we characterized the misuse. We calculated the proportion of individuals who did not have their own prescription, used prescription stimulants or opioids with alcohol, in greater amounts, more frequently, or for longer than prescribed.

We then estimated the associations between prescribed use or misuse and past year cocaine, methamphetamine, and heroin use with separate multivariable logistic regressions. Each regression included categorical variables for no-use, prescribed use, and misuse of prescription stimulants and opioids as well as controls for sociodemographic and health characteristics. We generated predictive margins to estimate the proportion of individuals within each category of prescription use who also used cocaine, methamphetamine, or heroin. We used an adjusted Wald test to assess whether rates of cocaine, methamphetamine, or heroin use were different between people who reported prescription stimulant prescribed use or misuse compared to prescription opioid prescribed use or misuse. Because the 2020 NSDUH data collection was affected by the COVID-19 pandemic, we also include a sensitivity analysis limited to 2015–2019 data (Appendix Tables 1–4).

All analyses included primary sampling unit, strata, and weight variables to account for NSDUH’s survey design. We used Stata 17 (StataCorp, College Station, TX) for all data management and analysis. Per the Hennepin Healthcare Research Institute’s Policy on using publicly available, deidentified data, this study is not human subjects research.

3. Results

3.1. Prevalence of prescription opioid and stimulant use and misuse

Our unweighted sample included 241,675 adult respondents surveyed between 2015 and 2020. More individuals reported prescribed use and misuse of prescription opioids (29.4 % and 4.0 %) than prescription stimulants (4.7 % and 2.0 %) (Table 1). Among individuals who reported any use of prescription stimulants a higher percentage (30 %) reported stimulant misuse compared to the percent of individuals reporting opioid misuse (12 %) among those who reported any use of prescription opioids. An annualized weighted total of 1.4 million (95 % CI: 1.3–1.5) people reported misusing both prescription stimulants and opioids, which represents 29 % of all individuals who reported prescription stimulant misuse.

Table 1.

Annualized weighted adults reporting prescription stimulant and opioid no use, prescribed use, and misuse (millions of individuals) – United States, 2015–2020.

Prescription stimulant use
 Total
No use Prescribed use Misuse
Prescription opioid use No use 157.2 (63.5 %) 5.3 (2.1 %) 2.3 (0.9 %) 164.9 (66.6 %)
(155.6–158.8) (5.1–5.5) (2.2–2.5) (163.2–166.6)
Use 66.6 (26.9 %) 5.2 (2.1 %) 1.1 (0.4 %) 72.9 (29.4 %)
(65.8–67.5) (4.9–5.4) (1.0–1.2) (72.0–73.8)
Misuse 7.3 (2.9 %) 1.1 (0.5 %) 1.4 (0.6 %) 9.8 (4.0 %)
(7.0–7.6) (1.0–1.2) (1.3–1.5) (9.5–10.2)
Total 231.1 (93.4 %) 11.6 (4.7 %) 4.9 (2.0 %)
(229.2–233.1) (11.2–12.0) (4.7–5.1)
Open in a new tab

3.2. Sociodemographic, health, and prescription misuse characteristics

Compared to people who misused prescription opioids, individuals who misused prescription stimulants were more likely to be white (77.2 % [95 % CI: 75.9–78.5] vs. 61.6 % [95 % CI: 61.0–62.3]) and 18 to 25 years old (45.8 % [95 % CI: 44.0–47.5] vs. 21.7 % [95 % CI: 20.7–22.7]) (Table 2). A higher proportion of individuals who misused prescription opioids identified as Hispanic (16.0 % [95 % CI: 14.9–17.3]) or Black (10.9 % [95 % CI: 10.1–12.1]) compared to individuals who misused prescription stimulants (11.6 % [95 % CI: 10.5–12.8] and 4.7 % [95 % CI: 4.0–5.4], respectively). Individuals who misused prescription stimulants were more likely to have private insurance (68.4 % [95 % CI: 66.9–69.8]) and incomes above 200 % of the federal poverty line (64.0 % [95 % CI: 62.4–65.6]), compared to individuals who misused prescription opioids (54.3 % [95 % CI: 52.8–55.7] and 57.9 % [95 % CI: 56.2–59.5], respectively). Rates of unstable housing and CLI did not differ among individuals who misused prescription stimulants (6.6 % [95 % CI: 5.8–7.5] and 11.1 % [95 % CI: 10.0–12.3]) or misused prescription opioids (6.1 % [95 % CI: 5.5–6.8] and 11.7 % [95 % CI:10.8–12.7]). Individuals who misused prescription opioids were more likely to report fair or poor health (19.9 % [95 % CI: 18.5–21.4]) compared to individuals who misused prescription stimulants (9.9 % [95 % CI: 8.8–11.0]).

Table 2.

Individual sociodemographic and health characteristics by prescription substance use categories – United States, 2015–2020.

Characteristic Weighted % (95 % CI)
Past year prescription stimulants
 Past year prescription opioids
No use Prescribed use Misuse No use Prescribed use Misuse
Weighted percentage 93.4 % (93.2–93.5) 4.7 % (4.5–4.8) 2.0 % (1.9–2.0) 66.6 % (66.3–66.9) 29.4 % (29.1–29.7) 4.0 % (3.8–4.1)
Male 48.4 (48.0–48.8) 42.0 (40.6–43.4) 56.3 (54.8–57.7) 49.9 (49.5–50.3) 43.9 % (43.3–44.6) 53.3 % (51.8–54.8)
Race/ethnicity
 White 62.9 (62.3–63.4) 74.0 (72.6–75.3) 77.2 (75.9–78.5) 61.6 (61.0–62.3) 67.8 (67.0–68.5) 67.2 (65.8–68.6)
 Black 12.3 (11.9–12.7) 7.9 (7.2–8.6) 4.7 (4.0–5.4) 11.6 (11.2–12.0) 12.8 (12.2–13.3) 10.9 (10.1–12.1)
 Hispanic 16.4 (16.0–16.9) 12.4 (11.3–13.6) 11.6 (10.5–12.8) 17.5 (17.1–17.9) 13.1 (12.6–13.7) 16.0 (14.9–17.3)
 Other 8.4 (8.2–8.7) 5.7 (5.1–6.4) 6.5 (5.9–7.3) 9.3 (9.0–9.6) 6.3 (6.1–6.6) 5.8 (5.2–6.5)
Age (years)
 18–25 12.8 (12.6–13.0) 20.4 (19.4–21.4) 45.8 (44.0–47.5) 15.0 (14.8–15.2) 10.0 (9.8–10.3) 21.7 (20.7–22.7)
 26–34 15.5 (15.2–15.7) 20.7 (20.0–21.5) 30.4 (28.6–32.3) 16.5 (16.2–16.8) 13.8 (13.5–14.2) 23.8 (22.7–24.9)
 35–49 24.7 (24.4–25.0) 26.1 (25.0–27.1) 17.2 (15.6–19.0) 24.7 (24.4–25.0) 24.2 (23.7–24.8) 27.2 (26.1–28.3)
 50+ 47.0 (46.6–47.5) 32.8 (31.4–34.3) 6.6 (5.2–8.5) 43.8 (43.4–44.3) 51.9 (51.1–52.7) 27.3 (25.6–29.0)
Income
 <100 % FPL 14.1 (13.8–14.4) 14.9 (13.9–15.8) 18.4 (17.1–19.9) 13.6 (13.3–14.0) 14.7 (14.2–15.2) 20.1 (19.0–21.3)
 100–200 % FPL 19.6 (19.3–19.9) 18.8 (17.5–20.1) 17.6 (16.2–19.0) 19.1 (18.8–19.4) 20.1 (19.6–20.5) 22.0 (20.7–23.4)
 >200 % FPL 66.4 (65.9–66.8) 66.4 (64.9–67.8) 64.0 (62.4–65.6) 67.3 (66.8–67.8) 65.2 (64.5–65.9) 57.9 (56.2–59.5)
Insurance status
 Private 65.8 (65.3–66.2) 67.3 (65.6–68.9) 68.4 (66.9–69.8) 67.2 (66.8–67.7) 64.5 (63.8–65.1) 54.3 (52.8–55.7)
 Medicaid 13.2 (12.9–13.4) 14.9 (13.8–16.1) 13.8 (12.5–15.2) 11.8 (11.5–12.0) 15.5 (15.1–16.0) 21.8 (20.6–23.1)
 Other 11.0 (10.7–11.2) 9.4 (8.4–10.5) 4.8 (4.2–5.5) 10.1 (9.9–10.4) 12.6 (12.2–13.0) 7.9 (7.0–8.9)
 Uninsured 10.1 (9.9–10.3) 8.4 (7.6–9.3) 13.0 (12.2–13.9) 10.9 (10.6–11.2) 7.5 (7.2–7.7) 16.1 (15.1–17.0)
Education
 Less than HS 12.7 (12.4–13.0) 10.3 (9.1–11.6) 6.9 (6.0–8.0) 12.7 (12.4–13.0) 11.7 (11.4–12.2) 14.1 (13.0–15.2)
 HS 25.7 (25.4–26.0) 20.2 (19.2–21.3) 19.4 (18.1–20.7) 25.0 (24.6–25.3) 26.1 (25.5–26.7) 25.8 (24.4–27.3)
 Some college 30.2 (29.9–30.5) 38.3 (37.0–39.7) 40.9 (39.3–42.5) 28.9 (28.5–29.3) 34.2 (33.6–34.8) 37.2 (35.6–38.8)
 College grad 31.4 (30.9–31.9) 31.2 (30.0–32.4) 32.8 (31.2–34.4) 33.4 (32.9–34.0) 28.0 (27.4–28.6) 23.0 (21.5–24.5)
Rural residence 14.7 (14.3–15.1) 13.7 (12.6–14.9) 10.2 (9.4 –11.1) 14.0 (13.6–14.5) 15.8 (15.3–16.4) 14.1 (13.1–15.2)
Unstably housed 2.1 (2.1–2.2) 3.9 (3.4–4.4) 6.6 (5.8–7.5) 2.0 (1.9–2.1) 2.5 (2.3–2.7) 6.1 (5.5–6.8)
Criminal legal involvement 2.6 (2.5–2.7) 4.8 (4.5–5.2) 11.1 (10.0–12.3) 2.2 (2.1–2.3) 3.3 (3.0–3.5) 11.7 (10.8–12.7)
Severe mental illness 4.1 (3.9–4.2) 13.0 (12.2–13.8) 15.7 (14.4–17.1) 3.2 (3.1–3.4) 6.5 (6.2–6.8) 16.4 (15.4–17.5)
Fair or poor health 14.0 (13.7–14.3) 17.2 (16.1–18.4) 9.9 (8.8–11.0) 10.5 (10.2–10.9) 21.2 (20.6–21.9) 19.9 (18.5–21.4)
Open in a new tab

We compared characteristics of misuse between individuals who reported prescription opioid or stimulant misuse. Individuals were more likely to misuse prescription stimulants without their own prescription (80.2 % [95 % CI: 78.8–81.6]) than prescription opioids (58.2 % [95 % CI: 56.7–59.7]) (Table 3). Conversely, compared to prescription stimulants, prescription opioids were more likely to be misused by taking greater amounts than prescribed (20.1 %; [95 % CI: 19.0–21.3] vs. 11.3 % [95 % CI: 10.2–12.5]), more frequently than prescribed (15.4 % [95 % CI: 14.4–16.4] vs. 7.1 % [95 % CI: 6.1–8.2]), and for longer than prescribed (13.4 % [95 % CI: 12.3–14.4] vs. 3.5 % [95 % CI: 2.9–4.1]). Alcohol was more commonly used with prescription stimulants (13.1 % [95 % CI: 12.0–14.2]) than prescription opioids (8.9 % [95 % CI: 8.1–9.7]). The sociodemographic, health, and misuse characteristics were largely unaffected when restricting the sample to 2015–2019 data (Appendix Tables 2 and 3).

Table 3.

Characteristics of prescription stimulant and opioid misuse – United States, 2015–2020.

Weighted % (95 % CI)
Prescription stimulant misuse Prescription opioid misuse
(N = 7685) (N = 11,941)
Without prescription 80.2 (78.8–81.6) 58.2 (56.7–59.7)
With alcohol 13.1 (12.0–14.2) 8.9 (8.1–9.7)
Greater amounts 11.3 (10.2–12.5) 20.1 (19.0–21.3)
More often 7.1 (6.1–8.2) 15.4 (14.4–16.4)
Longer than prescribed 3.5 (2.9–4.1) 13.4 (12.3–14.4)
Open in a new tab

The proportion of individuals who reported each type of misuse among those who reported prescription stimulant or opioid misuse.

3.3. Cocaine, methamphetamine, and heroin use among people with no prescription use, prescription use, and prescription misuse

Individuals with neither prescription opioid nor stimulant use had the lowest rates of cocaine, methamphetamine, and heroin use: 1.1 % (95 % CI: 1.0–1.2), 0.4 % (95 % CI: 0.4–0.5), and 0.1 % (95 % CI: 0.1–0.1), respectively (Table 4). Compared to prescribed use of opioids, prescribed use of stimulants was associated with higher rates of cocaine (3.4 % [95 % CI: 3.1–3.8] vs 2.1 % [95 % CI: 1.9–2.2], p < 0.001), methamphetamine (1.2 % [95 % CI: 1.0–1.4] vs 0.5 % [95 % CI: 0.4–0.6], p < 0.001), and heroin use (0.3 % [95 % CI: 0.2–0.4] vs 0.2 % [95 % CI: 0.2–0.3], p < 0.001). Among individuals who reported prescription stimulant misuse, cocaine use was twice as common than among individuals who reported prescription opioid misuse (12.0 % [95 % CI: 11.0–12.9] vs. 5.7 % [95 % CI: 5.1–6.3], p < 0.001). Among individuals who reported prescription opioid misuse, heroin use was more prevalent (2.1 % [95 % CI: 1.7–2.5]) compared to individuals with prescription stimulant misuse (0.6 % [95 % CI: 0.4–0.7], p < 0.001). Methamphetamine use did not differ between individuals reporting prescription stimulant misuse (2.4 % [95 % CI: 1.9–3.0]) and prescription opioid misuse (2.1 % [95 % CI: 1.7–2.5], p = 0.67). In a sensitivity analysis restricted to 2015–2019 data, the magnitude and statistical significance of these associations did not substantially change (Appendix Table 4).

Table 4.

Rates of past year cocaine, methamphetamine and heroin use by prescription substance use categories – United States, 2015–2020.

Characteristic Weighted % (95 % CI)
No use Past year prescription stimulants
 Past year prescription opioids
Prescribed use Misuse Prescribed use Misuse
Cocaine use 1.1 (1.0–1.2) 3.4 (3.1–3.8)a,c 12.0 (11.0–12.9)a,d 2.1 (1.9–2.2)a 5.7 (5.1–6.3)a
Methamphetamine use 0.4 (0.4–0.5) 1.2 (1.0–1.4)a,c 2.4 (1.9–3.0)a 0.5 (0.4–0.6) 2.1 (1.8–2.5)a
Heroin use 0.1 (0.1–0.1) 0.4 (0.3–0.5)b,c 0.6 (0.4–0.7)a,d 0.2 (0.2–0.3)a 2.1 (1.7–2.5)a
Open in a new tab

Each row represents a unique multivariable logistic regression model estimating a rates of use for the given substance (left column), controlling for past year stimulant use or misuse and past year prescription opioid use or misuse. Adjusted proportions were calculated using post-estimation predictive margins.

a

Different than no use p < 0.001.

b

Different than no use p < 0.01.

c

Different than prescription opioid use p < 0.001.

d

Different than prescription opioid misuse p < 0.001.

4. Discussion

In a nationally representative sample from 2015 to 2020, we found higher rates of cocaine, methamphetamine, and heroin use among individuals who reported either prescription stimulant prescribed use or misuse compared to no use. These findings are consistent with previous results demonstrating high rates of prescription stimulant misuse among individuals with methamphetamine or cocaine use (Jones, 2020; Mustaquim et al., 2021). Additionally, we show that a larger percentage of people who misuse prescription stimulants will use cocaine compared to people who misuse prescription opioids. We build upon results from several smaller surveys that identified a similar increasing risk of cocaine use among individuals with prescription stimulant use (3–4 times as likely) and misuse (13 times as likely) compared to no use (Kelly et al., 2014; Looby et al., 2014; Sepúlveda et al., 2011). This gradient of risk for cocaine and methamphetamine use mirrors heroin-specific findings (Jones, 2013). We show an increased risk of cocaine, methamphetamine, and heroin use for individuals with prescription misuse compared to prescribed use and for prescribed use compared to no use. Our findings emphasize the importance of screening for cocaine and methamphetamine use among patients who are prescribed, or suspected to misuse, stimulants.

We found associations between cocaine and heroin, but not methamphetamine use, and misuse of prescription substances with similar psychotropic effects. Cocaine use was twice as common among individuals with prescription stimulant misuse compared to prescription opioid misuse and heroin use was almost four-times as common among individuals with prescription opioid misuse compared to prescription stimulant misuse. These findings build on extensive opioid-related research, which has suggested prescription opioid misuse may contribute to heroin use (Cicero et al., 2014; Clayton et al., 2019; Jones, 2013; Lankenau, Teti, et al., 2012; Peavy et al., 2012; Pollini et al., 2011), by showing a similar relationship between prescription stimulant and cocaine use. Interestingly, the risk of methamphetamine use did not vary between people who reported prescription stimulant or opioid misuse. Although we cannot determine causal relationships with these data, this finding maybe due to differences in the social environment, such as experiencing unstable housing, or high rates of methamphetamine and opioid polysubstance use rather than methamphetamine’s specific psychotropic effect (Doran et al., 2018; Shearer et al., 2020). As overdose deaths involving cocaine and methamphetamine continue to rise, future research should further explore the divergent patterns of cocaine and methamphetamine use among individuals who also misuse prescription stimulants. Our findings suggest that different prevention policies tailored to cocaine and methamphetamine may be warranted.

We observed a high prevalence of prescription stimulant and opioid co-use. More than half of the individuals who reported prescription stimulant prescribed use or misuse also reported prescription opioid prescribed use or misuse. It may be important to discuss the risks and screen for opioid use, in addition to cocaine and methamphetamine use, among individuals who use prescription stimulants. This overlap between prescription substances is similar to recent findings of a rise in concurrent methamphetamine and heroin use (Ellis et al., 2018; Gladden et al., 2019; Jones et al., 2020). The prevalence of concurrent stimulant and opioid misuse warrants public health efforts that address the harms of substance use to account for possible co-use. This could include improving addiction treatment programs, which often address only a single substance use disorder, and expanding harm reduction programs to individuals who are prescribed stimulants.

Clinicians who provide care to patients who misuse prescription stimulants should be aware of the possibility of the use of multiple other substances and consider screening for additional substance use. The findings from this study inform populations who maybe at greater risk for prescription stimulant misuse. Misuse was more common among males, white individuals, young adults aged 18–25, and individuals experiencing unstable housing or recent CLI. Consistent with previous research, we also found that the majority of individuals who misused prescription stimulants did not have their own prescription (Compton et al., 2018; Lasopa et al., 2015; Schepis et al., 2019). This finding underscores the importance of discussing the risks of prescription diversion among patients prescribed stimulants and screening at-risk individuals regardless of whether they are prescribed stimulant medications. Brief clinical practice strategies may be effective at reducing the likelihood of stimulant diversion (Molina et al., 2020). Additionally, given the dramatic rise in counterfeit pills containing fentanyl, seized by law enforcement, individuals who misuse stimulants without their own prescription should be counseled on the risks of accidental exposure and overdose (Palamar et al., 2022).

This study has important limitations. As NSDUH relies on self-reported measures for substance use our results could be biased if individuals did not remember or were unwilling to share accurate substance use history. To reduce this bias, the NSDUH survey uses an Audio Computer Assisted Self-Interview Software to gather responses to sensitive questions. Due to the cross-sectional nature of NSDUH and because the study did not record the age at which a respondent began misusing prescription substances, we are unable to assess whether prescription stimulant or opioid misuse initially preceded, co-occurred, or followed cocaine, methamphetamine, or heroin use. Without this chronological information we cannot analyze whether prescription misuse led to other substance use, but we are able to estimate associations between current use. Additionally, NSDUH does not contain information regarding the medical diagnosis for which stimulants or opioids are prescribed. We, therefore, cannot control for these confounding health conditions. However, we did analyze measures of health such as severe mental illness and self-reported physical health. Finally, because of the COVID-19 pandemic, the 2020 NSDUH data collection underwent significant changes. Specifically, no data were collected between mid-March through September. Beginning in October, the NSDUH used web rather than in-person data collection. This may bias our results if the 2020 sample of respondents differed or if reported past-year substance use differently compared to respondents in previous years. However, including the most recent data is important to inform the public health response to a rapidly changing overdose crisis. Additionally, we include a sensitivity analysis limited to 2015–2019 data, which would not be affected by these methodological changes.

5. Conclusion

In a nationally representative sample, we found high rates of cocaine and methamphetamine use among individuals who used or misused prescription stimulants. Cocaine use was substantially higher among individuals who misused prescription stimulants compared to prescription opioids. As cocaine and methamphetamine involved overdose deaths continue to increase in the United States, individuals who use or misuse prescription stimulants may be at an increased risk. These findings further our understanding of the relationship between prescription use and other substances. These associations are important for the development of targeted screening, prevention, and harm reduction programs to reduce the morbidity and mortality that stimulant use causes. As the substance use crisis in the United States evolves and stimulants are increasingly involved, researchers and treatment providers need to understand the relationships between prescription stimulant misuse and the use of cocaine and methamphetamine.

Supplementary Material

Appendix

Funding

This work was supported by NIH MSTP grant T32 GM008244 (R.D.S).

Footnotes

Declaration of competing interest

None.

CRediT authorship contribution statement

Riley D. Shearer: Conceptualization, Methodology, Formal analysis, Writing – original draft. Abenaa Jones: Conceptualization, Writing – review & editing. Benjamin A. Howell: Conceptualization, Writing – review & editing. Joel E. Segel: Conceptualization, Writing – review & editing. Tyler N.A. Winkelman: Conceptualization, Data curation, Writing – review & editing, Supervision.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.jsat.2022.108894.

References

  1. Ballester J, Valentine G, & Sofuoglu M (2017). Pharmacological treatments for methamphetamine addiction: Current status and future directions. Expert Review of Clinical Pharmacology, 10(3), 305–314. 10.1080/17512433.2017.1268916 [DOI] [PubMed] [Google Scholar]
  2. Butler AJ, Rehm J, & Fischer B (2017). Health outcomes associated with crack-cocaine use: Systematic review and meta-analyses. Drug and Alcohol Dependence, 180, 401–416. 10.1016/j.drugalcdep.2017.08.036 [DOI] [PubMed] [Google Scholar]
  3. Chen L-Y, Crum RM, Strain EC, CalebAlexander G, Kaufmann C, & Mojtabai R (2016). Prescriptions, nonmedical use, and emergency department visits involving prescription stimulants. The Journal of Clinical Psychiatry, 77(3), e297–e304. 10.4088/JCP.14m09291 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Chen L-Y, Crum RM, Strain EC, Martins SS, & Mojtabai R (2015). Patterns of concurrent substance use among adolescent nonmedical ADHD stimulant users. Addictive Behaviors, 49, 1–6. 10.1016/j.addbeh.2015.05.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Ciccarone D (2021). The rise of illicit fentanyls, stimulants and the fourth wave of the opioid overdose crisis. Current Opinion in Psychiatry, 34(4), 344–350. 10.1097/YCO.0000000000000717 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Cicero TJ, Ellis MS, Surratt HL, & Kurtz SP (2014). The changing face of heroin use in the United States: A retrospective analysis of the past 50 years. JAMA Psychiatry, 71(7), 821–826. 10.1001/jamapsychiatry.2014.366 [DOI] [PubMed] [Google Scholar]
  7. Clayton HB, Bohm MK, Lowry R, Ashley C, & Ethier KA (2019). Prescription opioid misuse associated with risk behaviors among adolescents. American Journal of Preventive Medicine, 57(4), 533–539. 10.1016/j.amepre.2019.05.017 [DOI] [PubMed] [Google Scholar]
  8. Substance Abuse and Mental Health Services Administration, R. N. (2019). Key substance use and mental health indicators in the United States: Results from the 2018 National Survey on Drug Use and Health. HHS publication no. PEP19–5068, NSDUH Series H-54.82.
  9. Compton WM, Han B, Blanco C, Johnson K, & Jones CM (2018). Prevalence and correlates of prescription stimulant use, misuse, use disorders, and motivations for misuse among adults in the U.S. The American Journal of Psychiatry, 175(8), 741–755. 10.1176/appi.ajp.2018.17091048 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Doran KM, Rahai N, McCormack RP, Milian J, Shelley D, Rotrosen J, & Gelberg L (2018). Substance use and homelessness among emergency department patients. Drug and Alcohol Dependence, 188, 328–333. 10.1016/j.drugalcdep.2018.04.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Ellis MS, Kasper ZA, & Cicero TJ (2018). Twin epidemics: The surging rise of methamphetamine use in chronic opioid users. Drug and Alcohol Dependence, 193, 14–20. 10.1016/j.drugalcdep.2018.08.029 [DOI] [PubMed] [Google Scholar]
  12. Frederick TJ, Chwalek M, Hughes J, Karabanow J, & Kidd S (2014). How stable is stable? Defining and measuring housing stability. Journal of Community Psychology, 42(8), 964–979. 10.1002/jcop.21665 [DOI] [Google Scholar]
  13. Gladden RM, O’Donnell J, Mattson CL, & Seth P (2019). Changes in opioid-involved overdose deaths by opioid type and presence of benzodiazepines, cocaine, and methamphetamine—25 states, July–December 2017 to January–June 2018. MMWR. Morbidity and Mortality Weekly Report, 68(34), 737–744. 10.15585/mmwr.mm6834a2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hedegaard H, Miniño AM, & Warner M (2020). Drug overdose deaths in the United States, 1999–2019. NCHS Data Brief, 394, 1–8. [PubMed] [Google Scholar]
  15. Jones CM (2013). Heroin use and heroin use risk behaviors among nonmedical users of prescription opioid pain relievers – United States, 2002–2004 and 2008–2010. Drug and Alcohol Dependence, 132(1–2), 95–100. 10.1016/j.drugalcdep.2013.01.007 [DOI] [PubMed] [Google Scholar]
  16. Jones CM (2020). Patterns and characteristics of methamphetamine use among adults—United States, 2015–2018. MMWR. Morbidity and Mortality Weekly Report, 69. 10.15585/mmwr.mm6912a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Jones CM, Underwood N, & Compton WM (2020). Increases in methamphetamine use among heroin treatment admissions in the United States, 2008–17. Addiction, 115(2), 347–353. 10.1111/add.14812 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kampman KM (2019). The treatment of cocaine use disorder. ScienceAdvances, 5(10). 10.1126/sciadv.aax1532 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kelly BC, Wells BE, Pawson M, LeClair A, & Parsons JT (2014). Combinations of prescription drug misuse and illicit drugs among young adults. Addictive Behaviors, 39(5), 941–944. 10.1016/j.addbeh.2013.12.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Kessler RC, Barker PR, Colpe LJ, Epstein JF, Gfroerer JC, Hiripi E, Howes MJ, Normand S-LT, Manderscheid RW, Walters EE, & Zaslavsky AM (2003). Screening for serious mental illness in the general population. Archives of General Psychiatry, 60(2), 184–189. 10.1001/archpsyc.60.2.184 [DOI] [PubMed] [Google Scholar]
  21. Lankenau SE, Schrager SM, Silva K, Kecojevic A, Jackson Bloom J, Wong C, & Iverson E (2012). Misuse of prescription and illicit drugs among high-risk young adults in Los Angeles and New York. Journal of Public Health Research, 1(1), 6. 10.4081/jphr.2012.e6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Lankenau SE, Teti M, Silva K, Bloom JJ, Harocopos A, & Treese M (2012). Initiation into prescription opioid misuse amongst young injection drug users. International Journal of Drug Policy, 23(1), 37–44. 10.1016/j.drugpo.2011.05.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Lasopa SO, Striley CW, & Cottler LB (2015). Diversion of prescription stimulant drugs among 10–18-year-olds. Current Opinion in Psychiatry, 28(4), 292–298. 10.1097/YCO.0000000000000172 [DOI] [PubMed] [Google Scholar]
  24. Looby A, Kassman KT, & Earleywine M (2014). Do negative stimulant-related attitudes vary for prescription stimulants and cocaine among college students? Addictive Behaviors, 39(6), 1100–1105. 10.1016/j.addbeh.2014.03.012 [DOI] [PubMed] [Google Scholar]
  25. McCabe SE, West BT, Schepis TS, & Teter CJ (2015). Simultaneous co-ingestion of prescription stimulants, alcohol and other drugs: A multi-cohort national study of US adolescents. Human Psychopharmacology, 30(1), 42–51. 10.1002/hup.2449 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Molina BSG, Kipp HL, Joseph HM, Engster SA, Harty SC, Dawkins M, Lindstrom RA, Bauer DJ, & Bangalore SS (2020). Stimulant diversion risk among college students treated for ADHD: Primary care provider prevention training. Academic Pediatrics, 20(1), 119–127. 10.1016/j.acap.2019.06.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Mustaquim D, Jones CM, & Compton WM (2021). Trends and correlates of cocaine use among adults in the United States, 2006–2019. Addictive Behaviors, 120, Article 106950. 10.1016/j.addbeh.2021.106950 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. National Center for Health Statistics. (2022). U.S. overdose deaths in 2021 increased half as much as in 2020—But are still up 15%. Centers for Disease Control and Prevention. https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2022/202205.htm.
  29. Palamar JJ, Ciccarone D, Rutherford C, Keyes KM, Carr TH, & Cottler LB (2022). Trends in seizures of powders and pills containing illicit fentanyl in the United States, 2018 through 2021. Drug and Alcohol Dependence, 234, Article 109398. 10.1016/j.drugalcdep.2022.109398 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Peavy KM, Banta-Green CJ, Kingston S, Hanrahan M, Merrill JO, & Coffin PO (2012). “Hooked on” prescription-type opiates prior to using heroin: Results from a survey of syringe exchange clients. Journal of Psychoactive Drugs, 44(3), 259–265. 10.1080/02791072.2012.704591 [DOI] [PubMed] [Google Scholar]
  31. Pollini RA, Banta-Green CJ, Cuevas-Mota J, Metzner M, Teshale E, & Garfein RS (2011). Problematic use of prescription-type opioids prior to heroin use among young heroin injectors. Substance Abuse and Rehabilitation, 2, 173–180. 10.2147/SAR.S24800 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Schepis TS, Wilens TE, & McCabe SE (2019). Prescription drug misuse sources of controlled medications in adolescents RH = adolescent prescription misuse sources. Journal of the American Academy of Child and Adolescent Psychiatry, 58(7), 670–680. e4. 10.1016/j.jaac.2018.09.438 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Sepúlveda DR, Thomas LM, McCabe SE, Cranford JA, Boyd CJ, & Teter CJ (2011). Misuse of prescribed stimulant medication for ADHD and associated patterns of substance use: Preliminary analysis among college students. Journal of Pharmacy Practice, 24(6), 551–560. 10.1177/0897190011426558 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Shearer RD, Howell BA, Bart G, & Winkelman TNA (2020). Substance use patterns and health profiles among US adults who use opioids, methamphetamine, or both, 2015–2018. Drug and Alcohol Dependence, 214, Article 108162. 10.1016/j.drugalcdep.2020.108162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Substance Abuse and Mental Health Services Administration. (2020). 2019 national survey on drug use and health public use file codebook. [PubMed]
  36. Trivedi MH, Walker R, Ling W, dela Cruz A, Sharma G, Carmody T, Ghitza UE, Wahle A, Kim M, Shores-Wilson K, Sparenborg S, Coffin P, Schmitz J, Wiest K, Bart G, Sonne SC, Wakhlu S, Rush AJ, Nunes EV, & Shoptaw S (2021). Bupropion and naltrexone in methamphetamine use disorder. New England Journal of Medicine, 384(2), 140–153. 10.1056/NEJMoa2020214 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Vivolo-Kantor AM, Hoots BE, Seth P, & Jones CM (2020). Recent trends and associated factors of amphetamine-type stimulant overdoses in emergency departments. Drug and Alcohol Dependence, 216, Article 108323. 10.1016/j.drugalcdep.2020.108323 [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Wang Y, Cottler LB, & Striley CW (2015). Differentiating patterns of prescription stimulant medical and nonmedical use among youth 10–18 years of age. Drug and Alcohol Dependence, 157, 83–89. 10.1016/j.drugalcdep.2015.10.006 [DOI] [PubMed] [Google Scholar]
  39. Westmoreland DA, Goldshear JL, Carrico AW, & Grov C (2021). Associations of prescription stimulant misuse with subsequent methamphetamine use among a U.S. cohort of HIV-vulnerable sexual and gender minorities who have sex with men. Drug and Alcohol Dependence, 226, Article 108841. 10.1016/j.drugalcdep.2021.108841 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Appendix
NIHMS1847479-supplement-Appendix.docx (28.6KB, docx)

RESOURCES