Regional Disparities in Prescription Methamphetamine and Amphetamine Distribution Across the United States

Abstract

Objective:

The objectives of this report were to characterize the regional and state differences in prescription methamphetamine and amphetamine distribution in the US.

Methods:

Prescription methamphetamine and amphetamine distribution was obtained from the Drug Enforcement Administration for 2019.

Results:

Total per capita drug weight distribution of amphetamine was 4,000 times higher than methamphetamine. Regionally, total per capita drug weight for methamphetamine was highest in the West (32.2% of total distribution) and lowest in the Northeast (17.4%). The total per capita drug weight for amphetamine was highest in the South (37.0% of total distribution) and lowest in the Northeast (19.4%). Distribution of methamphetamine was 16.1% while amphetamine was 54.0% of its production quota.

Conclusion:

Overall, prescription amphetamine distribution was common while prescription methamphetamine distribution was rare. The patterns observed in distribution are likely the result of stigmatization, differences in accessibility, and the efforts of initiatives such as the Montana Meth Project.

Keywords

stimulants Desoxyn Adderall XR

Introduction

Methamphetamine, a potent amphetamine derivative, is a well-recognized psychostimulant that acts upon the central nervous system inducing feelings of euphoria, increased alertness, mood and concentration, as well as elevated interest in external stimuli (Kish, 2008). This highly addictive (Schedule II) drug has a higher lipid solubility, making it capable of crossing the blood-brain barrier rapidly, and produces a prolonged action due to greater elimination half-life, on the order of 10 to 20 hr, when compared to cocaine, which is measured in minutes to an hour, and other amphetamines (11–14 hr for d-AMP and l-AMP) (Galbraith, 2015; Salamanca et al., 2015; Steingard et al., 2020). Schedule II drugs are defined as substances that have accepted medical use and thus are prescribed or administered accordingly, however these substances are characterized by high abuse potential and risk for severe psychological and physical dependence (Lopez & Tadi, 2021). Once introduced into circulation, concentration of the drug, and its metabolite amphetamine, rapidly accumulates within the brain and leads to the release of various monoamines, primarily, dopamine, serotonin, and norepinephrine, which in turn affect neurochemical processes responsible for reward processing, motivation, and attention, ultimately promoting drug dependence (Karila et al., 2010; Siefried et al., 2020). Methamphetamine is available in many different forms, such as in crystalline hydrochloride salt form, referred to as crystal meth, or as a prescription drug in tablet form (Siefried et al., 2020). Extra-medical use of the drug is typically in crystalline form and occurs in significantly higher doses than what is prescribed orally as a controlled medical treatment. Faster onset of the drug is typically achieved via alternative methods of administration, such as intravenous, intranasal, vaginal, and inhalation, in which users consume higher doses for recreational use prompted by socio-cultural influences or for performance enhancement (Karila et al., 2010).

Neurotoxicity of methamphetamine exposure has been supported by abnormalities in brain structure and physiological manifestations, such as hallucinations, delusions, depression, suicidality and aggression (Karila et al., 2010). Furthermore, addiction has been known to occur faster than with cocaine and to a stronger extent in which a single exposure is enough to establish dependency (Karila et al., 2010). Unlike other stimulant drugs, drug-seeking behaviors for methamphetamine persist even after tolerance has been reached (Karila et al., 2010). Physiological effects have been reported to include neuronal tissue death and damage, dental disease, cardiovascular morbidity, stroke, and cognitive impairment (Karila et al., 2010). High risk sexual behaviors associated with methamphetamine use indirectly increases the prevalence of STIs, such as HIV infection (Karila et al., 2010). Other neurological manifestations of heavy meth use includes formications, in which there is a sensation of insects crawling on or under the skin, which may lead to skin-picking behaviors that form lesions and ulcers. Lack of hygiene combined with consistent disruption of wound-healing mechanisms has resulted in a high incidence of cellulitis and skin infection in those who misuse the drug. Furthermore, heavy methamphetamine use disrupts the immunological system, altering host immunity by increasing the pH of acidic organelles, which inhibits phagocytosis and antigen presenting processes essential in innate immunity, decreasing one’s ability to fight off infection (Salamanca et al., 2015). Overall, long-term and chronic methamphetamine use has shown detrimental psychosocial and physiological consequences making it a major public health concern.

Despite the addictive nature of the drug and its implications on public health, there are therapeutic uses for amphetamine, due to its ability to increase alertness and concentration, in the treatment of adult patients with attention-deficit hyperactivity disorder (ADHD) and narcolepsy. Compared to non-stimulant drugs such as clonidine and atomoxetine, stimulant drugs such as amphetamine-based agents (Adderall, Ritalin, Dexedrine) are more effective in treating adult-ADHD by increasing catecholamine availability in striatal and cortical brain regions (Faraone, 2018). The fine line between drug misuse and drug therapy can be noted by the prevalence of adults with ADHD who also suffer from methamphetamine misuse, even when amphetamine is being used as an effective treatment option. Substance misuse disorders have been noted to co-occur with ADHD and subsequent substance misuse has also been noted in which methamphetamine misuse replaces ADHD medication dependency (Chen et al., 2014; Zulauf et al., 2014). The major issue within this complicated relationship between the medical use of amphetamine and stimulant misuse disorders involving methamphetamine is that it has led to the stigmatization of both methamphetamine and amphetamine and consequently, the underreporting of use. Prior pharmacoepidemiological research has examined changes and regional disparities in amphetamine, but less is known for methamphetamine (Bokhari et al., 2005; Piper et al., 2018; Vaddadi et al., 2021). In this study, we aimed to demonstrate the variable weight distribution of methamphetamine and amphetamine across the United States and provide a regional analysis.

Methods

Procedures

The Drug Enforcement Administration’s (DEA) Automation of Reports and Consolidated Orders System (ARCOS) was used to obtain drug weight data for methamphetamine and amphetamine by US state for the year 2019, as well as the production quotas for the same year (Drug Enforcement Administration Diversion Control Division, 2018, 2019). This year was chosen as the most recent that this information was reported for both substances. Methamphetamine and amphetamine are both Schedule II controlled substances, which means transactions from manufacturers through the drug supply chain to point-of-sale distributors are required by law to be reported to ARCOS. Due to their structural similarity, amphetamine data was included for comparison to methamphetamine. ARCOS had also shown high-concordance with a state prescription drug monitoring program for ADHD medication (Bokhari et al., 2005). Our data was obtained specifically from the publicly available Reports 3, 4, and 7 of the 2019 Retail Drug Summary Report. Data regarding production quotas for 2019 was obtained from the DEA’s notice on the Established Aggregate Production Quotas for Schedule I and II Controlled Substances for 2019. Procedures were approved as exempt by the IRB at Geisinger.

Data Analysis

The total per capita quarterly drug distributions, measured as (mg) per 1,000 people were calculated for both methamphetamine and amphetamine. The 50 US states were divided into the following four regions based on the grouping used by the US Census Bureau: Northeast, South (including Washington DC), Midwest, and West (US Census Bureau Geography Division, 2013). The total per capita drug weights for each state and region, measured as mg per 1,000 people, were calculated for both methamphetamine and amphetamine. Heat maps were generated with http://www.heatmapper.ca/geomap/ (Babicki et al., 2016) using the total per capita drug weights measured as mg per 1,000 people. Per capita distribution of both substances was also expressed as a ratio relative to the lowest, nonzero, state. For each substance, the states were arranged from lowest to highest based on drug weight per capita and percentiles were calculated. Then the ratio of the drug weight per capita for the state at the 90th percentile compared to the drug weight per capita for the state at the 10th percentile was determined as an index of variation (Madera et al., 2022; Steinman et al., 2009). Data from retail drug purchases for methamphetamine and amphetamine was also converted to percentages and classified based on the business activity. These businesses included pharmacies, hospitals, practitioners, teaching institutions, mid-level practitioners, and narcotic treatment programs. The ratio of substance distributed in 2019 relative to production quotas for 2019 was determined for both drugs. Figures were prepared with GraphPad Prism, 9.3.1.

Results

In Figure 1, the total per capita quarterly drug distributions of both methamphetamine (+6.8%) and amphetamine (+5.8%) increased from Q1 to Q4. However, the increase was more consistent from quarter to quarter with amphetamine, but not so with methamphetamine. The total per capita drug distribution of methamphetamine in Q2 saw a decrease compared to Q1 (−5.1%), but was followed by increases from Q2 to Q3 (+11.3%) and Q3 to Q4 (+1.1%). The ratio of amphetamine to methamphetamine distribution was 3,976.9 in Q1, 4,298.6 in Q2, 3,908.8 in Q3, and 3,939.7 in Q4 (Mean = 4,031.0).

Figure 1.

Total per capita quarterly drug distribution of: (A) methamphetamine and (B) amphetamine in milligrams per 1,000 people in the US in 2019 as reported to the Drug Enforcement Administration’s Automated Reports and Consolidated Orders System.

Figure 2 shows the geographical distribution of each agent. In Montana, distribution of prescription methamphetamine was zero, but distribution of amphetamine was nonzero. Montana is also the only state where either of the drugs has a distribution of zero. The top (highest) and bottom (lowest) three states for each drug can be noted in Figure 2, but more easily identified in Supplemental Table 1, which expresses the per capita distributions as a ratio relative to the lowest, nonzero, state. Comparing the state with the highest distribution of prescription methamphetamine to the state with the lowest, Washington had 16.8 times more per capita distribution than Arkansas. For amphetamine, the range was not nearly as widespread, with Louisiana having only 4.92 times more per capita distribution than New Mexico. When the 90/10 ratio was determined for both substances, that is the ratio of the drug weights per capita for the states at the 90th and 10th percentiles, the following was observed. For methamphetamine, drug distribution in the state at the 90th percentile was 4.39-fold higher than that of the state at the 10th percentile. For amphetamine, the difference was 2.45-fold.

Figure 2.

Heat maps of the per capita drug weights of methamphetamine (left) and amphetamine (right) in milligrams per 1,000 people by US state in 2019.

In Figure 3, the total per capita drug weight of methamphetamine was greatest in the West, followed by the Midwest, then the South, and finally the Northeast. The total per capita drug weight of methamphetamine in the West was nearly twice as high as that in the Northeast. The total per capita drug weight of amphetamine was greatest in the South, followed by the Midwest, then the West, and finally the Northeast. Again, the total per capita drug weight of amphetamine in the highest region, the South, was nearly twice as high as that in the lowest region, the Northeast.

Figure 3.

Total per capita drug weights of: (A) methamphetamine and (B) amphetamine in milligrams per 1,000 people by region of the US in 2019. Heat maps of the total per capita drug weights of methamphetamine (bottom left) and amphetamine (bottom right) in milligrams per 1,000 people by region of the US in 2019.

For both methamphetamine and amphetamine, over 97% of retail drug purchases came from pharmacies. Of the remaining less than 3%, a majority of drug purchases for both substances were from hospitals. There were 39.1-fold more registrants that received amphetamine (66,475) than methamphetamine (1,702). The vast majority of both methamphetamine (97.30%) and amphetamine (97.60%) recipients were pharmacies. Hospitals accounted for 2.30% for methamphetamine and 2.37% for amphetamine recipients. Practitioners, mid-level practitioners, and teaching institutions only accounted for a combined total of 73 registrants, which made up the remaining 0.03% of amphetamine recipients. Comparing the total grams of each drug distributed via sales reported to ARCOS to the production quotas set for 2019, only 16.1% of methamphetamine allowed to be produced (for sale, not conversion) was distributed, while 54.0% of amphetamine allowed to be produced (for sale, not conversion) was distributed.

Discussion

There are three key findings from this novel pharmacoepidemiological report. The first being the regional variations in methamphetamine and amphetamine. The second being the 4000-fold difference between amphetamine and methamphetamine distribution, with amphetamine being most common. Finally, the third key finding was that for both schedule II substances as reported by ARCOS in 2019, distribution was remarkably lower compared to production quotas.

Finding 1: Regional Variations

Methamphetamine distribution was found to be highest in the Western and Midwestern regions of the US. These findings mirror previously found patterns of methamphetamine use that correlated with its location of illicit production from small toxic labs as well as superlabs (Gonzales et al., 2010; Hunt et al., 2006). However, despite the West and Midwest continuing to have the highest methamphetamine use rates, production and distribution of the drug is now believed to be more widespread across the US, with a doubling of illicit lab seizures in the South and fewer in the Northeast (Hunt et al., 2006; Sudakin & Power, 2009).

The region with the highest distribution of methamphetamine (West) had the second lowest distribution of amphetamine. Likewise, the region with the highest distribution of amphetamine (South) had the second lowest distribution of methamphetamine. The Northeast had the lowest distributions for both methamphetamine and amphetamine. Although it does not follow the pattern of the Northeastern region as a whole, Rhode Island as a state follows the inverse pattern between distribution of methamphetamine versus amphetamine, with one of the lowest distributions of methamphetamine, but one of the highest distributions of amphetamine. This is consistent with the altitude-methamphetamine use correlation and a second pattern. When The Comprehensive Methamphetamine Control Act (CMCA) of 1996 was enacted, which targeted illegal methamphetamine production but not pharmaceutical amphetamines, the use of prescribed amphetamines skyrocketed (Dollar, 2019). This pattern of low methamphetamine use with high amphetamine use was observed in a Rhode Island hospital where MDMA usage was more common than methamphetamine usage, which was zero during the time of the study, among trauma patients, but the incidence of MDMA and amphetamine alone was the same (Ward et al., 2011). Our results are also consistent with state psychostimulant (methylphenidate and amphetamine) distribution rates of 2000, in which Rhode Island oscillated within the higher quartile and 75th percentile above the national average (Bokhari et al., 2005).

Patterns of increased drug use in the West and Midwest including states such as Washington, Oregon, Utah, Wyoming, Colorado, North Dakota and Minnesota, may be explained by increases in adult ADHD cases due to revision of ADHD criteria, in which DSM-5 symptom domain thresholds provide better identification of adult ADHD symptoms and associated impairments than DSM-IV, which is most effective in setting the criteria for young children (Epstein & Loren, 2013). Lower drug distribution by weight can be noted in the states in the Southern and Northeastern regions of the country, such as Texas, Arkansas, Tennessee, Vermont, and West Virginia. Lower amphetamine distribution can be noted in the Western and Northeastern regions of the country. This was different from regional amphetamine use trends of 2016, in which use in Western regions was one-third lower compared to Northeastern and Midwestern regions (Piper et al., 2018). Using our findings to extend upon past research in which US amphetamine distributional variations from 2010 to 2017 demonstrated that the overall +67.5% rise was less pronounced in the West compared to other regions, we might draw the conclusion that amphetamine distribution continue to rise more slowly in the Western region (Vaddadi et al., 2021). Additionally, the lowest values of Daily Dosage/population (20 mg/day/person for amphetamine) were also reported within the Western region (Vaddadi et al., 2021). Previous studies using data from the National Health Interview Survey (NHIS) by the CDC found that from 1997 to 2016, weighted prevalence of ADHD diagnosis was highest in the Northeast (10.8%–13.6%, 95 CI) and lowest in the West (6.1%–7.8%, 95 CI) (Xu et al., 2018). This is consistent with other findings in which highest rates of ADHD diagnosis and medication use in children aged 3 to 17 years old for 2018 to 2019 were highest in Southern regions (10.97% and 7.52%, respectively) and lowest in Western regions (7.46% and 4.14%, respectively) (Bozinovic et al., 2021).

The results from this study highlight variations in drug distribution across the United States, with one of the most recognizable disparities being that of Montana in which no methamphetamine drug distribution was reported in 2019, despite Montana residing within the Western region and being surrounded by states showing the highest rates of prescription methamphetamine distribution per 1,000 people. One plausible explanation for the regional variations in amphetamine and methamphetamine distribution across the US could correlate to regional concentrations of younger physicians who are on average more likely to over-prescribe psychostimulants compared to older colleagues (Bokhari et al., 2005). Furthermore, regional differences in medical specialties could also account for these variations as areas with larger populations of psychiatrists could account for increased psychostimulant distribution (Bokhari et al., 2005). Additional research is necessary to determine if there is a strong correlation between either or both of these factors and the regional disparities we have identified.

Stigmatization, Substance Use Disorders, and Regional Variations

The regional patterns of prescription methamphetamine and amphetamine distribution, including the zero distribution of methamphetamine in Montana, may also be explained by the stigmatization of methamphetamine use and amphetamine-based medications used to treat ADHD, which may be discouraging physicians from recommending them as a therapeutic option. Stigmatization of drugs such as amphetamine and methamphetamine extends beyond the nature of their non-medical uses as it also encompasses the stigma around certain health conditions such as HIV and other STIs, including adult ADHD diagnoses. Studies regarding stigma around mental health disorders has shown that the public tends to believe that reported ADHD symptoms are often autonomous, leading them to discredit and undermine the diagnosis of affected individuals (Mueller et al., 2012). Adults suffering from ADHD are often labeled as infantile and socially objectionable, public stigma breeds self-stigma in those with ADHD, and in order to avoid peer-rejection, sufferers prefer to conceal symptoms (Godfrey et al., 2021; Mueller et al., 2012).

Stigmatization ultimately prevents ADHD sufferers from receiving treatment and allowing for mild symptoms to develop into severe psychiatric disabilities impacting social functioning (Godfrey et al., 2021; Mueller et al., 2012). In those who do seek medical treatment for ADHD, they are also susceptible to stigmatization and public mistrust of the medications available to them, specifically stimulant drugs such as methamphetamine. Among the most common concerns of ADHD medication is the risk of children and adults developing substance misuse disorders from exposure to stimulants. Stigmatizing attitudes in regard to ADHD medication make children and adults less likely to adhere to treatment and promotes noncompliance, which also negatively affects patients exhibiting help-seeking behaviors despite strong support and evidence that combined treatment of medication and psychotherapy is effective in ADHD management (Mueller et al., 2012). Even in cases in which substance misuse co-occurs with ADHD, stimulant drugs are still effective in treating ADHD and do not increase misuse potential for other drugs (Mariani & Levin, 2007). In fact, the use of stimulant drugs in treating childhood ADHD may decrease the likelihood an individual develops a substance use disorder (SUD) (Kooij et al., 2012).

Individuals suffering from ADHD are at increased risk of also suffering from SUDs with a prevalence of 10% to 24% in adults (Mariani & Levin, 2007). There exists the misperception that this occurs due to ADHD medication dependence rather than due to dopamine neurotransmission, a neurotransmitter also heavily implicated in addiction and associated neurobiological changes. Dopamine plays a major role in motivation and reward processing, as well as reinforcing drug effects, leading to compulsive behaviors in drug users (Volkow et al., 2007). In considering the impact that ADHD has on SUD, issues regarding stimulant based pharmacotherapy are presented. A major fact that is considered is how detrimental untreated ADHD is in patients with SUD, as proper management can prevent social deficits, lack of educational and job attainment, and development of drug addictions. Individuals suffering from both ADHD and SUD are less likely to adhere to rehabilitation treatments despite increased exposure compared to those without ADHD (Mariani & Levin, 2007). Furthermore, substance misuse begins at a younger age in those with ADHD and remission is harder to achieve (Mariani & Levin, 2007). When both comorbidities are treated, there exists better outcomes. Although amphetamine-based medications have higher misuse potential in patients with SUD, substitution with sustained-release methamphetamine demonstrated reduced positive urine samples and cocaine cravings in a placebo-controlled randomized clinical trial (Mariani & Levin, 2012).

Health-related stigmas, such as in SUD, lead to the rejection and humiliation of people suffering from diseases that have been labeled by socio-cultural standards as unrespectable health conditions. Additionally, stigmas also negatively impact services offered to patients to treat their conditions if they are associated with addictive drugs such as methamphetamine, amphetamine, and methadone (Livingston et al., 2012). Intervention methods geared toward reducing stigma around SUDs prevent self-stigma and destructive behaviors by those devalued by the public. They aim to educate and build social acceptance, and in turn prevent substance misuse more effectively than stigmatization does. In restructuring these attitudes about substance misuse, negative stereotypes guiding public policy, allocation of health-care expenses, and treatment of patients by physicians can be reduced (Livingston et al., 2012).

Positive attitudes toward substance misuse treatment allows for prevention of infections and STIs commonly associated with risky behaviors and lack of hygiene in SUD via harm reduction intervention methods. Intravenous administration of drugs such as methamphetamine account for 60% of emerging Hepatitis C cases and one-third of new HIV transmissions (McNeely et al., 2006). Providing those who are unable to stop using drugs with sterile syringes via exchange allows for safer syringe practice and has been reported to be most effective in reducing HIV transmission. Furthermore, it allows for a foundation for other forms of intervention and treatments to be promoted, such as methadone maintenance in treating heroin addiction (McNeely et al., 2006).

In relation to the methamphetamine distribution data in Montana, which was zero, the effect of the Montana Meth Project (MMP) may serve as an explanation, especially considering how amphetamine distribution for the same year was still within the lower range compared to other states. We can speculate that the distribution, or lack of, for methamphetamine and amphetamine in this state may be from stigmatization of both prescription and illicit methamphetamine use caused by the MMP initiative. The objective of the MMP was to educate and discourage youth from using illicit meth by stigmatizing use and making it socially unacceptable. As previously discussed, this stigmatization, in combination with heavy advertising against amphetamine use using stereotyped images of what people using meth may look like, may have been preventing health care providers from recommending it as an ADHD treatment due to fear of public push back (Anderson, 2010). Studies have shown that social stigma serves as a major effector in physicians not recommending certain drugs and patient refusal to take them (Wu et al., 2022). Furthermore, results of a study conducted using data from 1999 to 2009 Youth Risk Behavior Surveillance System indicated that the project’s impact on curbing meth use was statistically non-significant (Anderson, 2010).

Regional differences in ADHD diagnosis, treatment, and access to care can be further related to stigma by examining ethnic and racial disparities. One population based, multisite longitudinal study found that ADHD diagnosis and medication use disparities were likely related to underdiagnosis or undertreatment of African American and Latino children (Coker et al., 2016). Additionally, the disparities observed were noted to be less likely due to overtreatment and overdiagnosis of White children (Coker et al., 2016). Thus, another plausible explanation for the regional distribution differences observed may be due to larger White populations between states, where White people are more likely than Black or Hispanic minorities to be diagnosed and treated with ADHD medication, resulting in higher ADHD medication distribution and higher prescription rates. More research must be done in order to examine the extent that factors such as public or internalized stigma, negative attitudes toward mental health services, and varying cultural perceptions affect access to care or help-seeking behaviors in minorities compared to White counterparts against other demographics. Furthermore, examining differences in regional stigma regarding amphetamine and methamphetamine usage for ADHD treatment warrants further study as it could help explain the regional distribution trends observed.

Other alternative theories to explain the regional distribution patterns we found include regional differences in accessibility to ADHD diagnosis, care coordination, and treatment. Shortages in mental health professionals in rural areas of the US along with limited access to care may serve as a significant barrier to obtaining ADHD treatment and services. Research has demonstrated that rural residents are more likely to be uninsured compared to urban residents, which may serve as a financial barrier. Furthermore, rural residents with potential mental health problems remained less likely to use mental health services, with non-Hispanic minorities being less likely to obtain care compared to non-Hispanic Whites. The lower mental health spending observed among rural residents could suggest lower use of psychotherapy (Ziller et al., 2010). Future research must be done in order to further analyze the effects that accessibility has on regional distribution of amphetamine and methamphetamine for ADHD.

Finding 2: Total Distribution of Amphetamine Versus Methamphetamine

Prescription amphetamine distribution was found to be 4000-fold more common than methamphetamine. The Drug and Chemical Evaluation Section on Methamphetamine provided by the DEA indicates there is only one current licit methamphetamine product, Desoxyn, which is available in 5, 10, and 15 mg tablets, that is FDA-approved in managing ADHD and obesity (Drug Enforcement Administration Diversion Control Division, 2020). The FDA access data on Desoxyn (methamphetamine hydrochloride tablets) warns about limiting use for ADHD and obese patients, and consideration of prescribing Desoxyn should come after other alternative pharmacotherapies, or treatment programs, have been deemed unsuccessful (Recordati Rare Diseases Inc, 2015). The limited use of methamphetamine in treating ADHD is consistent with the prevalence of amphetamine distribution in this pharmacoepidemiological report.

The increasing popularity of telemedicine may also provide insight upon methamphetamine and amphetamine distribution trends. These health platforms connect patients with healthcare professionals online, allowing for increased access to care by removing physical barriers in seeking treatment. One retrospective cross-sectional study on encounters for ADHD via direct-to-consumer telemedicine found that from 2016 to 2018, ADHD visits increased 500%, with 43% of ADHD-related encounters resulting in prescription of non-controlled medications (Hohman et al., 2020). These findings coincide with data from the National Mental Health Services Survey showing that mental health facilities increased telemedicine services from 22.2% in 2015 to 68.7% in 2020. Furthermore, between 2019 to 2020, the provision of telemedicine services increased from 38% to 68.7%, respectively for mental health facilities (Alvarado, 2021). More research must be done to determine how much of the delivery of telemedicine services were for ADHD consultations and treatment.

Telemedicine platforms such as Cerebral Inc. offer online prescriptions to controlled medications such as amphetamine-based stimulants and benzodiazepams, which has led to US federal investigation on prescribing practices (Blum, 2022). Over-prescribing of these controlled medications by telemedicine companies may explain distributional variations. Additionally, a cross-sectional study analyzing the accessibility of amphetamine-dextroamphetamine through digital pharmacies determined that of the 62 pharmacies found via popular web search engines, 61 pharmacies were determined to be rogue and unclassified, 100% of which were selling drugs without a prescription, quantity limit, or requirement of a health-related assessment (Penley et al., 2021). Illegitimate online pharmacies and telehealth companies overprescribing controlled substances with high potential for abuse can exacerbate diversion and nonmedical use of amphetamine and methamphetamine.

Finding 3: Distribution Versus Production Quotas

The third key finding of this report was the notable difference between distribution of the two prescription drugs and their production quotas. The DEA establishes an aggregate production quota (APQ) for Schedule I and II controlled substances annually for the following year, which may have one revision (Drug Enforcement Administration Diversion Control Division, 2017). This APQ aims to be representative of the national need and will set the manufacturing quotas, and in-turn the procurement quotas, as well (Drug Enforcement Administration Diversion Control Division, 2017). In order to determine the appropriate APQ, the DEA considers applications from manufacturers, FDA estimates, and prescription audit data (Drug Enforcement Administration Diversion Control Division, 2017). The APQ data that was compared to the total grams of methamphetamine and amphetamine distributed via sales reported to ARCOS was strictly that “for sale” and not “for conversion,” in an attempt to gain a more accurate comparison. However, since the APQ does not only aim to reflect the medical, scientific, and research needs of the US, but also its industrial, export, and reserve needs, the gap between the production quotas and distribution might be explained by distribution to another source not reported in the ARCOS retail drug summary reports (Drug Enforcement Administration Diversion Control Division, 2017).

Conclusion

This study evaluated the regional variations in methamphetamine and amphetamine drug distribution within the United States. Disparities in drug distribution data as extracted through the comprehensive ARCOS database demonstrated that methamphetamine in the Western and Midwestern portions of the country (excluding Montana) showed increased drug distribution when compared to other parts. In terms of amphetamine data, the opposite was true, in which distribution was lowest in the Western region. The most notable was the state of Montana in which methamphetamine distribution was zero. We also found that amphetamine distribution was 4,000-fold more common than methamphetamine. These variations in distribution are likely present due to stigmatization and accessibility differences to amphetamine-based medications, however, additional research is required to understand the scope of this relationship, as well as many other potential correlations suggested. A potential follow-up to this study might also explore regional differences in prescriptions for antidepressants and anxiety medications, since adult ADHD may often be hidden behind mood or anxiety symptoms (Kooij et al., 2012). In addressing stigma revolving ADHD diagnosis and treatment options as well as assessing intervention options for comorbidities such as SUD, distribution may change as public health policies and health care provider recommendations are heavily correlated to public opinion. Future research must be done in order to quantify the effect that initiatives such as the Montana Meth Project have on health care provider recommendation of ADHD stimulant medications. Future studies may also aim to investigate possible causes for the disproportion between distribution and production quotes as reported by ARCOS in 2019. Furthermore, identifying unique prescribers of methamphetamine may also explain the regional variations and distribution trends present.

Supplemental Material

sj-docx-1-jad-10.1177_10870547231177467 – Supplemental material for Regional Disparities in Prescription Methamphetamine and Amphetamine Distribution Across the United States

Supplemental material, sj-docx-1-jad-10.1177_10870547231177467 for Regional Disparities in Prescription Methamphetamine and Amphetamine Distribution Across the United States by Sarah D. Lopera, Victoria M. O’Kane, Jessica L. Goldhirsh and Brian J. Piper in Journal of Attention Disorders

Footnotes

Author Contributions

Conceptualization (SDL, BJP), Data curation (SDL, VMO), Formal analysis (SDL, VMO), Visualization (SDL, VMO), Writing—original draft (SDL, VMO, JLG), Writing—review & editing (all). All authors have read and agreed to the published version of the manuscript.

Declaration of Conflicting Interest

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: BJP was part of an osteoarthritis research team from 2019 to 2021 supported by Pfizer and Eli Lilly. The other authors have no conflicts of interest.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research received no external funding. Software was provided by NIH (T32 ES007060-31A1).

Institutional Review Board Statement

Procedures were exempt as reviewed by the IRB of Geisinger.

Informed Consent Statement

Not applicable.

Data Availability Statement

Publicly available datasets were analyzed in this study. This data can be found here:

ORCID iD

Brian J. Piper

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Sarah D. Lopera received her Bachelor of Science in Cell & Molecular Biology from John Jay College of Criminal Justice. She also received her Master of Biomedical Sciences from Geisinger Commonwealth School of Medicine. Her research interests include pharmacoepidemiology as well as neurological diseases and disorders.

Victoria M. O’Kane received her Bachelor of Science and Arts from the University of Texas at Austin, and her Master of Biomedical Sciences from Geisinger Commonwealth School of Medicine. Her research interests include pharmacoepidemiology and sports medicine.

Jessica L. Goldhirsh, MD, is an assistant professor at Geisinger Commonwealth School of Medicine and the assistant chair of psychiatry education for Geisinger Health System and GCSOM. Clinically, she works as an outpatient adult psychiatrist.

Brian J. Piper is an assistant professor of Neuroscience at Geisinger Commonwealth School of Medicine. Research interests include pharmacoepidemiology, particularly of controlled substances, and bioethics. Teaching interests include psychopharmacology, statistics, and public health.

References

Alvarado

H. A.

(2021). Telemedicine services in substance use and mental health treatment facilities (The CBHSQ Spotlight). Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/report/telemedicine-services

Anderson

D. M.

(2010). Does information matter? The effect of the meth project on meth use among youths. Journal of Health Economics, 29(5), 732–742. https://doi.org/10.1016/j.jhealeco.2010.06.005

Babicki

Arndt

Marcu

Liang

Grant

J. R.

Maciejewski

Wishart

D. S.

(2016). Heatmapper: Web-enabled heat mapping for all. Nucleic Acids Research, 44(W1), W147–W153. https://doi.org/10.1093/nar/gkw419

Blum

(2022). The hazards of prescribing A.D.H.D. drugs online. The New York Times. 2022. https://www.nytimes.com/2022/05/13/well/mind/cerebral-adhd-medication-tiktok.html

Bokhari

Mayes

Scheffler

R. M.

(2005). An analysis of the significant variation in psychostimulant use across the US. Pharmacoepidemiology and Drug Safety, 14(4), 267–275.

Bozinovic

McLamb

O’Connell

Olander

Feng

Haagensen

Bozinovic

(2021). U.S. National, regional, and state-specific socioeconomic factors correlate with child and adolescent ADHD diagnoses pre-COVID-19 pandemic. Scientific Reports, 11(1), 22008–8.

Chen

L. Y.

Strain

E. C.

Alexandre

P. K.

Alexander

G. C.

Mojtabai

Martins

S. S.

(2014). Correlates of nonmedical use of stimulants and methamphetamine use in a national sample. Addictive Behaviors, 39(5), 829–836. https://doi.org/10.1016/j.addbeh.2014.01.018

Coker

T. R.

Elliott

M. N.

Toomey

S. L.

Schwebel

D. C.

Cuccaro

Tortolero Emery

Davies

S. L.

Visser

S. N.

Schuster

M. A.

(2016). Racial and ethnic disparities in ADHD diagnosis and treatment. Pediatrics, 138(3), e20160407. https://doi.org/10.1542/peds.2016-0407

Dollar

C. B.

(2019). Criminalization and drug “wars” or medicalization and health “epidemics”: How race, class, and neoliberal politics influence drug laws. Critical Criminology, 27, 305–327. https://doi.org/10.1007/s10612-018-9398-7

10.

Drug Enforcement Administration Diversion Control Division. (2017). Pharmaceutical training seminars: UN reporting and quota section. Department of Justice Drug Enforcement Administration (p. 40). Retrieved January, 20 2023, from https://www.deadiversion.usdoj.gov/mtgs/pharm_train/conf_2017/april_2017/dang_2.pdf

11.

Drug Enforcement Administration Diversion Control Division. (2018). Established aggregate production quotas for Schedule I and II controlled substances and assessment of annual needs for the list I chemicals ephedrine, pseudoephedrine, and phenylpropanolamine for 2019. United States: Department of Justice Drug Enforcement Administration, 83(Number 248), 67348–67354. https://deadiversion.usdoj.gov/fed_regs/quotas/2018/fr1228.htm

12.

Drug Enforcement Administration Diversion Control Division. (2019). ARCOS drug retail summary reports. Department of Justice Drug Enforcement Administration (p. 385) Report No.: 01-07. Retrieved December, 8 2021, from https://www.deadiversion.usdoj.gov/arcos/retail_drug_summary/report_yr_2019.pdf

13.

Drug Enforcement Administration Diversion Control Division. (2020). Drug & Chemical Evaluation Section: Methamphetamine. Department of Justice Drug Enforcement Administration (p. 1). https://www.deadiversion.usdoj.gov/drug_chem_info/meth.pdf

14.

Epstein

J. N.

Loren

R. E.

(2013). Changes in the definition of ADHD in DSM-5: Subtle but important. Neuropsychiatry, 3(5), 455–458. https://doi.org/10.2217/npy.13.59

15.

Faraone

S. V.

(2018). The pharmacology of amphetamine and methylphenidate: Relevance to the neurobiology of attention-deficit/hyperactivity disorder and other psychiatric comorbidities. Neuroscience and Biobehavioral Reviews, 87, 255–270. https://doi.org/10.1016/j.neubiorev.2018.02.001

16.

Galbraith

(2015). The methamphetamine problem: Commentary on . . . psychiatric morbidity and socio-occupational dysfunction in residents of a drug rehabilitation centre. BJPsych Bulletin, 39(5), 218–220. https://doi.org/10.1192/pb.bp.115.050930

17.

Godfrey

Fuermaier

A. B. M.

Tucha

Butzbach

Weisbrod

Aschenbrenner

Tucha

(2021). Public perceptions of adult ADHD: Indications of stigma? Journal of Neural Transmission, 128(7), 993–1008.

18.

Gonzales

Mooney

Rawson

R. A.

(2010). The methamphetamine problem in the United States. Annual Review of Public Health, 31, 385–398. https://doi.org/10.1146/annurev.publhealth.012809.103600

19.

Hohman

J. A.

Martinez

K. A.

Anand

Martyn

Rood

Rothberg

M. B.

(2020). Use of direct-to-consumer telemedicine for attention-deficit hyperactivity disorder. Journal of General Internal Medicine, 35(11), 3392–3394.

20.

Hunt

Kuck

Truitt

(2006). Methamphetamine use: Lessons learned. National Institute of Justice (p. 76). Report No.: 209730. Retrieved Accessed January 20, 2022, from https://www.ojp.gov/pdffiles1/nij/grants/209730.pdf

21.

Karila

Weinstein

Aubin

H. J.

Benyamina

Reynaud

Batki

S. L.

(2010). Pharmacological approaches to methamphetamine dependence: A focused review. British Journal of Clinical Pharmacology, 69(6), 578–592. https://doi.org/10.1111/j.1365-2125.2010.03639.x

22.

Kish

S. J.

(2008). Pharmacologic mechanisms of crystal meth. Canadian Medical Association Journal, 178(13), 1679–1682. https://doi.org/10.1503/cmaj.071675

23.

Kooij

J. J.

Huss

Asherson

Akehurst

Beusterien

French

Sasané

Hodgkins

(2012). Distinguishing comorbidity and successful management of adult ADHD. Journal of Attention Disorders, 16(5 Suppl), 3S–19S. https://doi.org/10.1177/1087054711435361

24.

Livingston

J. D.

Milne

Fang

M. L.

Amari

(2012). The effectiveness of interventions for reducing stigma related to substance use disorders: A systematic review. Addiction, 107(1), 39–50. https://doi.org/10.1111/j.1360-0443.2011.03601.x

25.

Lopez

M. J.

Tadi

(2021). Drug enforcement administration drug scheduling. StatPearls Publishing. https://www.ncbi.nlm.nih.gov/books/NBK557426/

26.

Madera

J. D.

Ruffino

A. E.

Feliz

McCall

K. L.

Davis

C. S.

Piper

B. J.

(2022). Declines and pronounced state disparities in prescription opioid distribution in the United States. medRxiv. Advance online publication. https://doi.org/10.1101/2021.12.02.21266660.

27.

Mariani

J. J.

Levin

F. R.

(2007). Treatment strategies for co-occurring ADHD and substance use disorders. American Journal on Addictions, 16(Suppl 1), 45–56. https://doi.org/10.1080/10550490601082783

28.

Mariani

J. J.

Levin

F. R.

(2012). Psychostimulant treatment of cocaine dependence. Psychiatric Clinics of North America, 35(2), 425–439. https://doi.org/10.1016/j.psc.2012.03.012.

29.

McNeely

Arnsten

J. H.

Gourevitch

M. N.

(2006). Sterile syringe access and disposal among injection drug users newly enrolled in methadone maintenance treatment: A cross-sectional survey. Harm Reduction Journal, 3, 8. https://doi.org/10.1186/1477-7517-3-8

30.

Mueller

A. K.

Fuermaier

A. B.

Koerts

Tucha

(2012). Stigma in attention deficit hyperactivity disorder. Attention Deficit and Hyperactivity Disorders, 4(3), 101–114. https://doi.org/10.1007/s12402-012-0085-3

31.

Penley

Chen

H. H.

Eckel

S. F.

Ozawa

(2021). Characteristics of online pharmacies selling Adderall. Journal of the American Pharmaceutical Association, 61(1), e103–e109.

32.

Piper

B. J.

Ogden

C. L.

Simoyan

O. M.

Chung

D. Y.

Caggiano

J. F.

Nichols

S. D.

McCall

K. L.

(2018). Trends in use of prescription stimulants in the United States and Territories, 2006 to 2016. PLoS One, 13(11), e0206100.

33.

Recordati Rare Diseases Inc. (2015). Medication Guide: Desoxyn. United States: U.S. Food and Drug Administration (p. 16). https://www.accessdata.fda.gov/drugsatfda_docs/label/2017/005378s034lbl.pdf

34.

Salamanca

S. A.

Sorrentino

E. E.

Nosanchuk

J. D.

Martinez

L. R.

(2015). Impact of methamphetamine on infection and immunity. Frontiers in Neuroscience, 8, 445. https://doi.org/10.3389/fnins.2014.00445

35.

Siefried

K. J.

Acheson

L. S.

Lintzeris

Ezard

(2020). Pharmacological treatment of methamphetamine/amphetamine dependence: A systematic review. CNS Drugs, 34(4), 337–365. https://doi.org/10.1007/s40263-020-00711-x

36.

Steingard

Taskiran

Connor

D. F.

Markowitz

J. S.

Stein

M. A.

(2020). Correction to: New formulations of stimulants: An update for clinicians. Journal of Child and Adolescent Psychopharmacology, 29, 324–339. https://doi.org/10.1089/cap.2019.0043.correx

37.

Steinman

M. A.

Yang

K. Y.

Byron

S. C.

Maselli

J. H.

Gonzales

(2009). Variation in outpatient antibiotic prescribing in the United States. The American Journal of Managed Care, 15(12), 861–868.

38.

Sudakin

Power

L. E.

(2009). Regional and temporal variation in methamphetamine-related incidents: Applications of spatial and temporal scan statistics. Clinical Toxicology, 47(3), 243–247. https://doi.org/10.1080/15563650802516160

39.

US Census Bureau Geography Division. (2013). Census bureau regions and divisions with state FIPS codes. US Department of Commerce, Economics, and Statistic Administration (p. 2). Retrieved January 25, 2022, from https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf.

40.

Vaddadi

S. M.

Czelatka

N. J.

Gutierrez

B. D.

Maddineni

B. C.

McCall

K. L.

Piper

B. J.

(2021). Rise, and pronounced regional variation, in methylphenidate, amphetamine, and lisdexamfetamine distribution in the United States. PeerJ, 9, e12619.

41.

Volkow

N. D.

Fowler

J. S.

Wang

G. J.

Swanson

J. M.

Telang

(2007). Dopamine in drug abuse and addiction: Results of imaging studies and treatment implications. Archives of Neurology, 64(11), 1575–1579. https://doi.org/10.1001/archneur.64.11.1575

42.

Ward

J. A.

Zuckerman

Adams

C. A.

Napoli

(2011). Amphetamine use in Rhode Island Hospital trauma patients. The American Journal of Emergency Medicine, 29(5), 569–571. https://doi.org/10.1016/j.ajem.2011.02.026

43.

L. T.

John

W. S.

Morse

E. D.

Adkins

Pippin

Brooner

R. K.

Schwartz

R. P.

(2022). Opioid treatment program and community pharmacy collaboration for methadone maintenance treatment: Results from a feasibility clinical trial. Addiction, 117(2), 444–456. https://doi.org/10.1111/add.15641

44.

Strathearn

Liu

Yang

Bao

(2018). Twenty-year trends in diagnosed attention-deficit/hyperactivity disorder among US children and adolescents, 1997-2016. JAMA network open, 1(4), e181471.

45.

Ziller

E. C.

Anderson

N. J.

Coburn

A. F.

(2010). Access to rural mental health services: Service use and out-of-pocket costs. The Journal of Rural Health, 26(3), 214–224. https://doi.org/10.1111/j.1748-0361.2010.00291.x

46.

Zulauf

C. A.

Sprich

S. E.

Safren

S. A.

Wilens

T. E.

(2014). The complicated relationship between attention deficit/hyperactivity disorder and substance use disorders. Current Psychiatry Reports, 16(3), 436. https://doi.org/10.1007/s11920-013-0436-6

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB