Elsevier

Neuropharmacology

Volume 87, December 2014, Pages 91-96
Neuropharmacology

Invited review
Epidemiology of stimulant misuse and abuse: Implications for future epidemiologic and neuropharmacologic research

https://doi.org/10.1016/j.neuropharm.2014.04.020Get rights and content

Highlights

  • Stimulants vary widely with respect to rates of misuse, abuse, addiction, and overdose.

  • Illicit cocaine and methamphetamine have the highest risk of addiction.

  • Prescription stimulant misuse is relatively uncommon, e.g., to aid concentration.

  • Epidemiologic differences in rates of misuse and abuse among stimulants suggest the influence of neuropharmacology.

Abstract

Stimulants are a diverse array of drugs that range from everyday caffeine to prescription medications and illicitly manufactured street drugs. The surveillance of misuse and abuse of stimulants many times confounds prescription and illicit street drugs such that the data are not specific enough to guide mitigation efforts or assess their impact. This review highlights the surveillance efforts that are conducted in the United States (US) for stimulant misuse and abuse. These surveillance efforts include national level surveys as well as reporting systems such as Poison Centers and emergency departments. This epidemiologic analysis has implications for interpreting the current known neuropharmacology of stimulants and possibly informing future neuropharmacology research that may contribute to a better understanding of potential neuropharmacologic factors influencing differing patterns of use, abuse, and adverse consequences associated with various stimulants.

This article is part of the Special Issue entitled ‘CNS Stimulants’.

Introduction

The drugs known collectively as “stimulants” are a diverse category including caffeine and relatively weak prescription stimulants such as mazindol and phentermine, which are not the focus of this review. Rather, this review will address the stronger stimulants, including those approved for the treatment of attention deficit/hyperactivity disorder (ADHD) (methylphenidate and various amphetamine molecules) and illicitly manufactured crack cocaine and methamphetamine formulations. These drugs are regulated as Schedule II drugs under the Controlled Substances Act (CSA) in the United States (US) and comparable schedules in other countries. Schedule II is reserved for drugs that carry the highest risk of abuse and dependence yet also are approved for medicinal use. Illicitly produced methamphetamine (“ice”) and crack cocaine are not approved for medicinal use, but they are also placed in Schedule II because pharmaceutical methamphetamine and cocaine do have approved medicinal uses (Drug Enforcement Administration, 2014, Spillane and McAllister, 2003).

The Schedule II stimulants methylphenidate, amphetamines, and cocaine are characterized with similar abuse potential profiles under a variety of laboratory tests of abuse liability, and they share generally similar pharmacologic actions as discussed in this issue of Neuropharmacology (Calderon and Klein, 2014, Zhou and Kreek, 2014, Lukas, 2014, Romach et al., 2014). Outside the laboratory, however, these drugs are associated with widely different patterns of use, risk of substance use disorders (American Psychiatric Association, 2013), and adverse effects including overdose leading to emergency room visits. For example, as discussed in this review, methylphenidate and prescription amphetamine products indicated for the treatment of ADHD are infrequently the primary drug of abuse cited by people presenting for treatment for substance abuse or as a cause of overdose as compared to illicitly manufactured methamphetamine (e.g., “ice”) or cocaine (e.g., “crack”) (O'Brien, 2011, Substance Abuse and Mental Health Services Administration, 2013, Zosel et al., 2013). Clearly the mechanisms of action and general pharmacology of these drugs do not appear to explain these differences, although variations in reinforcing effects perhaps related to speed of absorption to the brain and other pharmacologic differences cannot be entirely ruled out [see also (Calderon and Klein, 2014, Romach et al., 2014)].

Are there subtle but perhaps important neuropharmacologic differences among these drugs that help explain the differing patterns and risks of abuse? Are the differences better explained by social and environmental factors, cost, access, drug formulation, route of administration, population, or reasons for use? Four decades of surveillance and epidemiologic analyses may help to understand and explain these differences. What can we learn from the epidemiology that might be considered in neuropharmacologic investigations? What can we learn from current epidemiologic understanding that may be considered in future surveillance approaches? Addressing these two questions is the focus of this brief review.

Epidemiologic analysis requires reliable, valid, and relevant surveillance that keeps pace with an epidemic as it unfolds over time and across populations. It is clear that trends in stimulant misuse and abuse have changed dramatically over the past half century teaching us much about the importance of factors far beyond the pharmacology of the drugs as determinants of which drugs are used, how they are used, patterns of use within individuals, and consequences associated with various types of stimulant misuse and abuse. Unfortunately, the most frequently cited surveillance methods have not always kept pace with changing patterns of use and abuse and therefore, the resulting policy analyses rely on methods and data that may be of diminished relevance to current and evolving patterns of stimulant abuse.

In order to have an accurate and adequate understanding of the scope and scale of any ongoing public health problem, there needs to be a substantial, systematic surveillance effort in place; it must provide both consistent elements for comparative purposes over time as well as evolving components to keep pace with evolving trends in drug use form, patterns and reasons. Addressing the problem with science-based interventions places further demands on surveillance, specifically that it include information such as the reasons for use and other factors associated with use, including those that might be considered risk factors and protective factors.

With an appropriate surveillance system, one can track trends over time, detect new problems as they occur, and lay the foundation for interventions to prevent and control misuse and abuse, and mitigate unintended and undesired consequences. This is increasingly important for prescription drugs since they have legitimate medical uses. Intervention strategies that may reduce misuse and abuse, but also reduce the availability of the medications for patients that need them, can result in more harm than good for patients with legitimate medical need.

One example of surveillance that assesses both positive and negative factors influencing misuse and abuse is the nearly four decades of the Monitoring the Future (MTF) Survey (Johnston et al., 2013). This survey not only provides estimates of prevalence and trends, but it also has highlighted factors that are considered in drug control policy and prevention interventions (e.g., the finding that perception of harm is inversely associated with rates of use of specific substances). Tobacco control policy provides an example of how such data can be applied. Building on the MTF findings, more comprehensive surveillance efforts were developed to understand further the development and course of tobacco use and dependence in the 1990s. This resulted in a collaborative effort among tobacco control researchers and federal agencies including the Centers for Disease Control and Prevention and the National Institute on Drug Abuse to develop measures of cigarette smoking dependence and risk factors that would be used in surveys (Centers for Disease Control and Prevention, 1994). The questions that were developed were then used in many of the US federal surveys as well as state-based and other surveillance efforts and have become essentially standardized methods for measuring cigarette smoking behaviors.

The use of these questions consistently across surveys and over time allows for the collection of data that can be compared and trends to be evaluated. This level of consistently and systematically collected data on use provides public health advocates and policy makers with solid data upon which to address an important public health problem as well as monitor the effects of environmental and policy interventions, and to guide the improvement of interventions. In contrast, the MTF data on drug use, specifically prescription drug use, are complicated by combining many drugs into one question (often including both licit and illicit substances such as illicitly manufactured methamphetamine and prescription methylphenidate). The MTF is also limited in that its methods and instruments were not developed to rapidly evolve and provide quick (e.g., quarterly) dissemination of findings and therefore provide limited utility in guiding policy changes as problems arise with drugs as they come on both the licit and illicit markets. Thus, the surveillance systems that are used to monitor drug misuse and abuse in the US vary in the level of specificity for substances, the breadth of substances investigated (e.g., prescription/OTC/illicit), as well as the definitions used to identify misuse and abuse.

Epidemiologic contributions to understanding and controlling substance abuse are further limited by a dearth of comparative international data on trends and patterns of drug use and abuse. By contrast, the epidemiology of communicable diseases such as influenza, malaria and HIV AIDS is supported by a relatively comprehensive and cohesive global network of monitoring as provided through the World Health Organization's Collaborating Centers. Data collection on drug misuse and abuse is not conducted systematically or consistently worldwide, which limits the understanding of the scope of problems with specific drugs in different countries. These limitations, nationally and internationally, must be considered when evaluating trends and patterns of misuse and abuse.

A broad range of surveillance instruments and approaches are presently in use to track trends in substance abuse and guide risk management interventions to mitigate misuse and abuse (Dart, 2009, Dasgupta and Schnoll, 2009). Although these are not uniformly applied across drug classes, or standardized, US data sources can be used to provide an illuminating picture of stimulant drug misuse and abuse. The National Survey on Drug Use and Health (NSDUH) is an annual household-based survey of the US population aged 12 years and older, which is used to estimate national prevalence statistics. It includes questions regarding non-medical use of stimulant drugs and queries lifetime use of some specific drugs. It does not ask about specific drugs for past year or past month, but rather asks about “stimulants” as a category separate from cocaine and methamphetamine. These data are the most frequently cited for estimating the prevalence of drug misuse and abuse at a national level. The prevalence of non-medical use of prescription stimulants from the 2012 NSDUH are shown in Fig. 1

The estimated prevalence of non-medical use of prescription stimulants increases with age until the mid-30 s and then declines. Past month non-medical use (considered current use) prevalence is 1.2% or less in all age groups. Given that these rates are for the combined category of all stimulant medications, non-medical use for any individual medication would be expected to be lower.

The MTF Survey is administered in selected schools among 8th, 10th, and 12th grade students. Students in 8th grade are generally age 13–14; 10th grade students are approximately 15–16 years old, and 12th grade students are 17–18 years old. In 2012, 7.9% of the 12th grade students reported past year non-medical use of “amphetamines,” which includes methamphetamine. This proportion is higher than that reported by 16–17 year olds (2.4%) and even higher than 18–20 year olds (3.9%) in the NSDUH. By comparison, past year use of cocaine was 2.9% among 12th grade students in MTF and 1.6% (16–17 year olds) and 4.5% (18–20 year olds) in the NSDUH. The discrepant estimates derived from these two surveys were also found by Biondo and Chilcoat for non-medical use of Oxycontin (Biondo and Chilcoat, 2014). As assessed on MTF, the rate was 2.5–3.0 times higher than from the NSDUH. Likely explanations for the different estimates include survey administration (school versus home) and question wording, the nature of which limits the ability to compare the data and leaves one questioning which survey—if either—provides an accurate estimate of the true rates of misuse and abuse. Nevertheless, it is clear that non-medical use of stimulants is not a highly prevalent behavior among adolescents in either survey, especially when compared to other classes of drugs.

In addition to population-based surveys, there are other surveillance efforts in the US that can be used to monitor drug abuse. These efforts include the Drug Abuse Warning Network Emergency Department (DAWN-ED), Treatment Episode Data Set (TEDS), Poison Centers (PCs), and several proprietary surveillance systems (Researched Abuse and Addiction-Related Surveillance [RADARS®] System and the National Addictions Vigilance Intervention and Prevention Program [NAVIPPRO®]). Each of these surveillance efforts provides important information regarding drug abuse and has been used to supplement the data provided by MTF and NSDUH. In fact, the RADARS System was initially developed to track abuse of a specific opioid drug at the brand level because there were no federal data available (Cicero et al., 2005).

DAWN collected data from hospital ED visits that involve non-medical use of prescription and over-the-counter medications as well as dietary supplements. Non-medical use is defined in the DAWN system as: (1) taking a higher than prescribed or recommended dose of a pharmaceutical (contrary to directions or labeling); (2) taking a pharmaceutical prescribed for another individual; (3) malicious poisoning of one individual by another; or (4) substance abuse involving pharmaceuticals. A location-stratified sample of 233 hospitals contributed data for the 2011 annual report; sample weights were applied to estimate national figures taking into account hospital size and ownership, metropolitan area and underlying population. DAWN-ED data cannot be used to estimate prevalence since the system relies on spontaneous visits to these facilities. The most recent DAWN-ED data (2011) for stimulants and other drugs are shown in Table 1.

A large proportion of the approximately 1.2 million drug related ED visits included in 2011 involved the non-medical use of CNS-acting pharmaceutical products. Stimulants were noted in 3.3% of all drug related ED visits for non-medical drug use. In comparison, analgesics were involved in 46.1% of visits.

TEDS reports on admissions to drug abuse treatment facilities (although not all facilities are included) that involve abuse of alcohol, prescription and illegal drugs. The data are not representative of all individuals abusing certain substances, but they do provide information regarding those who have reached a point in their behavior that they are seeking, or being compelled into treatment through the criminal justice system (e.g., drug courts and involuntary commitment). If substances become more common among TEDS reports, then that may indicate an even larger abuse problem in the population at large since it is generally believed that less than 10% of those who abuse drugs ever enter treatment (Substance Abuse and Mental Health Services Administration, 2009).

Data from TEDS shows low and fairly stable rates of admission for primary abuse of amphetamines other than methamphetamine as well as stimulants that are not amphetamine from 1995 to 2011 (Fig. 2). There has been an increase in admissions to treatment for primary abuse of methamphetamine as well as opioids over this same time period. Of note, during this period there were new treatment options adopted for opioid dependence in the US, which was not the case with stimulants. The availability and acceptability of treatment may also have impacted rates of admissions.

Poison centers (PC) are state-level call centers staffed by clinical specialists in toxicology and pharmacology. PCs respond to spontaneous inquiries from the public, health care professionals, and public health agencies. Given the spontaneous reporting aspect of the calls, PC data are not usable for calculating prevalence estimates. Nevertheless, these data are available in near real-time and are valued as an early warning system since the data are highly drug specific.

Calls received by PCs are compiled on a calendar year basis and released in annual reports. The most recent annual report was for 2011 (Bronstein et al., 2012), which reported on 2,334,004 human exposures. Human exposure calls related to stimulants were reported as a combined category with “street drugs,” a category composed of prescription stimulants as well as drugs such as methylenedioxymethamphetamine (MDMA; Ecstasy), cocaine and “bath salts,” which are synthetic amphetamines (Table 2).

In the most recent annual PC report, trends in exposure calls were examined for the time period 2001–2011. Of the 25 categories that had the most rapid increases in exposure calls, “Stimulants and Street Drugs” ranked 13th with an average increase of 1231 (95% CI: 326–2136) exposure calls annually. “Stimulants and Street Drugs” were associated with 169 fatalities in 2011, 41 of which were single substance exposures.

Data from the proprietary systems (RADARS and NAVIPPRO) are not available in the public domain. Nevertheless, some pharmaceutical companies that have subscriptions to these services as well as the researchers who manage these systems have published some of the data (Sembower et al., 2013).

Section snippets

Implications for drug control policy and risk management

Although we would like to believe that drug control policy as well as other policies are based on data that are collected from well-designed studies, this is most often not the case. Policies related to the misuse, abuse and diversion of drugs are frequently based on anecdotal reports that are often exaggerated in the media (Jenkins, 1999). These reports are then cited by politicians and regulatory agencies as the basis for laws and regulations. For example, from 2002 to 2012 the NSDUH showed

Challenges

As demonstrated by the data presented above, the lack of consistent and systematic data collection is problematic nationally and internationally for assessing misuse and abuse of stimulants, differences among stimulants, and the determinants of these differences. Nonetheless, these surveillance data suggest that factors such as the form of the drug and the route by which it is used, and the reasons for use are important determinants of patterns of use and adverse consequences such as the

Conclusion

This epidemiologic analysis has implications for efforts to effectively mitigate the risks of misuse, abuse, and diversion. The data sources that are available to monitor abuse of stimulant medications are far from comprehensive in scope, and they do not employ standard categories for drugs or measurements of/definitions for misuse and abuse. We strive here to highlight some of the most common issues with surveillance of self-reported stimulant use, and much work remains to be done to devise a

Disclosure

The authors consult for or have consulted in the past three years through Pinney Associates to pharmaceutical companies regarding the regulation, development and post-marketing surveillance of stimulant products and other CNS drugs of abuse. This manuscript was independently prepared without support for or input from any such commercial interests.

Acknowledgments

The authors thank Mark Sembower for his assistance with federal survey data analysis.

References (26)

  • C.D. Bryant et al.

    Csnk1e is a genetic regulator of sensitivity to psychostimulants and opioids

    Neuropsychopharmacology

    (2012)
  • Centers for Disease Control and Prevention

    Cigarette smoking among adults – United States, 1992, and changes in the definition of current cigarette smoking

    Morb. Mortal. Wkly. Rep.

    (1994)
  • N. Dasgupta et al.

    Signal detection in post-marketing surveillance for controlled substances

    Drug Alcohol Depend.

    (2009)
  • Cited by (0)

    View full text