Abstract
Background and Objectives:
Methamphetamine use is increasing in the United States, potentially including the simultaneous injection of methamphetamine with heroin (goofball). We compared demographic, behavioral, contextual, and health factors among people who inject drugs (PWID) in the Seattle area and who reported that their main drug was goofball, heroin, or methamphetamine.
Methods:
We used data from 2017 and 2019 cross-sectional surveys of clients at Public Health–Seattle & King County’s syringe services program (N=792).
Results:
Among PWID participants, 55.3% reported using goofball in the last 3 months, and the proportion reporting goofball as their main drug doubled between 2017 (10.3%) and 2019 (20.1%, p<0.001). The goofball group had the highest proportions of people who were age <30, women, homeless or unstably housed, and recently incarcerated. PWID whose main drug was goofball reported considerable health risks and morbidity. Witnessing an opioid overdose was most commonly reported by participants whose main drug was goofball. This group also reported naloxone possession and use in an overdose situation more than other participants. The majority of participants were interested in reducing or stopping their opioid and stimulant use.
Discussion and Conclusions:
Among PWID, using goofball as a main drug doubled over two years and was characterized by contextual and individual factors that increase risk of morbidity and mortality.
Scientific Significance:
This is the first study to characterize goofball use as a main drug. Clinical and public health efforts to diminish morbidity associated with opioid use need to integrate interventions that address co-use of methamphetamine.
BACKGROUND AND OBJECTIVES
Methamphetamine use is increasing in the wake of the opioid crisis in the United States (U.S.). Increases in the use of this highly addictive stimulant have been documented in the health literature1,2 as well as in the national media.3 In Denver, Colorado, and Seattle, Washington, the increase in methamphetamine use has predominantly involved a growing proportion of people who inject drugs (PWID) using both methamphetamine and heroin, either separately or in a single injection commonly known as a goofball.1,2 (Goofball can also be smoked.) Data from San Diego, California, and Tijuana, Baja California, Mexico have also demonstrated high levels of co-injection of methamphetamine and heroin.4
Although existing literature provides some insight into the characteristics and circumstances of people who inject goofball, the available data remain very limited. We previously published an analysis of data from syringe services program (SSP) clients in the Seattle area between 2009 and 2017, and found that people who used goofball were significantly more likely than other PWID to be young, homeless, inject daily, and self-report an opioid overdose.2 Additional data on specific injection behaviors, other health outcomes, and interest in treatment among people who inject goofball are needed to understand how to most effectively implement harm reduction and substance use treatment efforts. In addition, it is important to focus on people whose primary drug is goofball to determine how the needs of this potentially high acuity group may differ from people predominantly using other drugs.
The aim of this analysis was to assess how persons who consider goofball to be their main drug differ from persons whose main drug is heroin or methamphetamine alone in their injection risk behaviors, health outcomes, interest and experience with drug treatment, and in the contextual factors affecting their lives. Given the higher risk environments observed among people who use methamphetamine and heroin together, we hypothesized that people whose main drug was goofball would report higher levels of injection risk behaviors and adverse health outcomes (e.g., overdose and abscesses), but lower levels of treatment use and interest than people who primarily use heroin or methamphetamine alone.
METHODS
Data Source
This analysis utilized survey data from clients at Public Health – Seattle & King County (PHSKC) SSPs in 2017 and 2019. PHSKC conducts biennial cross-sectional surveys of SSP users to monitor drug use behaviors and health conditions among its clients. Most clients are PWID seeking harm reduction supplies, but clients also include people who were obtaining supplies for others or engaged in on-site substance use treatment. Methods and results from the 2017 and earlier surveys have been previously published.2,5–7
PHSKC conducted the survey at two fixed-site SSP locations in Seattle and a mobile unit in south King County, Washington. Over two-week periods each summer, trained SSP employees and volunteers attempted to recruit all clients for a voluntary survey. Because there was no way to indicate which clients had already participated or declined to participate, clients were offered survey participation at each subsequent visit and asked if they had already completed the survey. Staff ensured that all clients, including those who previously participated and those who were not interested, received the services they were seeking. Participants gave verbal consent and could decline to answer any question. Interviewers read survey questions to participants and recorded responses directly into a REDCap database or first on a paper survey.8 Participants were offered a small candy at the conclusion of the survey.
The survey was performed as a public health surveillance activity for the PHSKC HIV/STD program and did not require review by an Institutional Review Board. The analysis was reviewed and approved by the University of Washington’s Human Subjects Division (STUDY00010571).
Study Sample
SSP staff approached 838 SSP clients in 2017 and 779 clients in 2019 to complete the surveys; 427 and 432, respectively, agreed to participate (51.0% cooperation rate in 2017, 55.5% in 2019). Because clients could have been asked to participate multiple times, this is likely an underestimate of the actual cooperation rate.
Measures
Goofball and Other Drug Use
We defined any drug use in the last 3 months by whether a participant indicated using, injecting, and/or smoking each drug (in the following order): heroin by itself; methamphetamine by itself; goofball (methamphetamine and heroin mixed together); powder cocaine by itself; crack cocaine by itself; speedball (cocaine and heroin mixed together); opiate medications like OxyContin, Vicodin, methadone, and buprenorphine; benzodiazepines and downers like Valium, Xanax, Klonopin, Soma; and fentanyl. A follow-up question asked which of these drugs was the participant’s “main” drug, which was not further defined. Based on interviewer feedback, a participant’s choice usually reflected the drug most commonly used. Frequency of use for each drug was measured by the number of days used in the last 7 days and available in 2019 only. We included participants who indicated that their main drug was goofball, heroin by itself, or methamphetamine by itself in analyses comparing characteristics of people across these three groups.
Demographic Characteristics
Age was measured continuously, and we categorized it into roughly 10-year age groups (18–29, 30–39, 40–49, 50+). We categorized a participant’s gender as being a woman (including transgender women), man (including transgender men), or a combined group of non-binary or other gender. Men who have sex with men (MSM) included both cisgender and transgender men who reported having sex with men in the last 12 months. We assessed race and ethnicity by calculating the proportion of participants that selected each identity. Participants could select more than one race/ethnicity and thus could be represented in multiple groups. We also measured housing status (stable housing or homeless/unstably housed), current health insurance (public, private, or other), and incarceration in the last year.
Drug Injection Behaviors and Drug Treatment Use and Interest
We used data on the number of injection days in the last week to calculate if a participant injected daily. We also calculated the average number of drug injections per day. We created dichotomous variables for any syringe or other injection equipment sharing in the last 3 months based on the number of people with whom they reported each behavior. We created dichotomous variables for injecting while alone and injecting in a public setting by combining responses of “some of the time,” “most of the time,” and “always” (vs. “never”). We estimated the proportion of participants who reported ever injecting into their femoral vein or jugular vein in the last 3 months. We calculated years since first injection by subtracting a participant’s age at first injection from their current age. We estimated the proportion of participants that were currently getting treatment for their drug use, and if so, what type of treatment. We measured interest in reducing or stopping use of opioids or stimulants among people who reported using each type of drug. Participants were classified as interested if they responded “very” or “somewhat” interested (vs. “not sure” or “not interested”).
Health Conditions and Overdose Experiences
We calculated the proportion of participants who reported a series of health conditions in the last year: an abscess or skin infection (asked as separate questions in 2017); an infected blood clot or blood infection; endocarditis; a sexually transmitted infection (STI), excluding HIV or hepatitis C virus, HIV, or pregnancy (women only). We constructed dichotomous variables to calculate the prevalence of an opioid or stimulant overdose in the last year and if a participant had observed someone else overdose on opioids or stimulants using data collected on the number of times a participant had experienced each outcome. (The definitions for each type of overdose are provided in Table 3.) We also estimated the proportion of participants who possessed naloxone in the last three months, and if so, if it had been used in an overdose situation.
Table 3.
Health conditions and overdose experiences by main drug used in the last three months among people who inject drugs, Public Health - Seattle and King County syringe services program clients, 2017–2019 (N=720)
| Main Drug Used, Last 3 Months | ||||
|---|---|---|---|---|
| Goofball N=120 # (%) | Heroin N=464 # (%) | Methamphetamine N=136 # (%) | p-value1 | |
| Health Conditions | ||||
| Abscess or skin infection, last 12 mos. | 71 (59.7) | 263 (56.7) | 51 (37.5) | <0.001 |
| Infected blood clot or blood infection, last 12 mos. | 18 (15.0) | 51 (11.0) | 9 (6.6) | 0.097 |
| Endocarditis, last 12 mos. | 7 (5.9) | 10 (2.2) | 0 (0.0) | 0.00911 |
| Sexually transmitted infection, last 12 mos.2 | 1 (0.9) | 12 (2.6) | 20 (14.7) | <0.00111 |
| HIV3 | 4 (3.6) | 8 (1.8) | 30 (23.4) | <0.00111 |
| Pregnancy, last 12 mos.4 | 2 (4.1) | 4 (2.5) | 4 (12.1) | 0.03711 |
| Overdose Experiences | ||||
| Self-reported opioid overdose, last 12 mos.5,6 | 29 (24.2) | 110 (23.8) | 14 (20.3) | 0.802 |
| Witnessed opioid overdose, last 12 mos. | 87 (73.1) | 284 (61.7) | 65 (47.8) | <0.001 |
| Possessed naloxone, last 3 mos. | 102 (85.0) | 331 (71.5) | 67 (49.3) | <0.001 |
| Naloxone used in overdose situation, last 3 mos.7 | 61 (59.8) | 172 (52.0) | 28 (41.8) | 0.071 |
| Self-reported stimulant overdose, last 12 mos.8,9 | 40 (33.3) | 89 (23.5) | 53 (39.6) | 0.001 |
| Witnessed stimulant overdose, last 12 mos.10 | 21 (51.2) | 92 (36.4) | 31 (43.7) | 0.141 |
Abbreviations: mos., months; HIV, human immunodeficiency virus; no., number; IQR, interquartile range [25th-75th]
P-value is for a χ2 test, unless otherwise indicated.
Excludes HIV and hepatitis C.
Restricted to participants who had received an HIV test and knew results (n=676).
Among women (2017 and 2019) and transwomen (2019) only (n=244); data are missing for 4 participants.
Defined as “when someone’s breathing slows down or stops, and they can’t wake up.”
Restricted to participants who reported any opioid use (n=653).
Restricted to participants who reported possessing naloxone (n=500).
In 2017, defined as “overdosing or overamping on meth or cocaine which usually looks like a heart attack, stroke, seizure, intense overheating or really extreme, sudden psychosis.” In 2019, defined by either “felt like you were having a heart attack, stroke, or seizure while on meth” or “felt like you were losing your mind, manic, or psychotic while on meth.”
Restricted to participants who reported any stimulant use (n=651).
2017 data only.
P-value is for a Fisher’s exact test.
Data Analysis
All analyses were restricted to SSP clients who reported any drug injection in the last three months and completed the full survey in 2017 (N=398) or 2019 (N=394, total N=792). In this sample restricted to those who inject, we calculated the frequency of use of individual drugs between participants who reported any goofball use and those who reported no goofball use. Participants who did not report that goofball, heroin by itself, or methamphetamine by itself was their main drug were excluded from all subsequent analyses (n=72). In this further restricted sample (N=720), we assessed differences in participant demographics, injection behaviors and treatment use, and health conditions and overdose experiences between SSP clients based on their main drug: goofball, heroin by itself, or methamphetamine by itself. We used Pearson’s chi-square tests to assess differences between categorical variables and Fisher’s exact tests if cell sizes were ≤5. We compared medians using the Kruskal-Wallis rank test. Missing data made up <5% of total answers per question. Estimates with p-values <0.05 were deemed statistically significant. Analyses were conducted using Stata/SE 16 (StataCorp LLC, College Station, TX).
RESULTS
Goofball and Other Polysubstance Use Trends
The majority (55.3%) of participants in the sample restricted to those who inject (N=792) reported using any goofball in the last 3 months, and 15.2% reported that goofball was their main drug. Among participants who reported any goofball use, 26.9% stated that goofball was their main drug, 59.1% said heroin, and 6.9% said methamphetamine. The proportion of PWID participants reporting that goofball was their main drug nearly doubled (10.3% vs. 20.1%, p<0.001) between 2017 and 2019. At the same time, there was no significant change between 2017 and 2019 in the proportion reporting any goofball use (54.3% vs. 56.4%, p=0.326), any heroin use (86.7% vs. 85.8%, p=0.549), any methamphetamine use (77.9% vs. 79.2%, p=0.528), or any fentanyl use (13.3% vs. 16.5%, p=0.453) in the last 3 months. The proportionate increase in goofball as a main drug was similar across each of these drug use groups. Participants who reported any goofball use in the last 3 months reported using goofball a median of 5 days a week, while those who reported that goofball was their main drug used it a median of 7 days a week. Nearly all participants who used goofball in the last 3 months reported injecting goofball (98.9%) and 22.0% reported smoking goofball.
Higher proportions of participants who used any goofball use in the last 3 months reported using many other drugs than those who did not use goofball. As shown in Figure 1, among participants who used goofball in the last 3 months, nearly all (97.3%) also used heroin by itself and the vast majority (89.2%) used methamphetamine by itself. Higher proportions of participants who used goofball in the last 3 months also used powder cocaine, speedball, fentanyl, and benzodiazepines.
Figure 1.
Other drug use reported by people who inject drugs stratified by whether they used any goofball in the last 3 months, Public Health – Seattle and King County syringe services program clients, 2017-2019 (N=792)
Sociodemographics
All subsequent analyses were further restricted to participants who reported that their main drug was goofball, heroin, or methamphetamine (N=720). The majority (65.1%) of these participants were younger than 40 years, approximately one-third (34.5%) were women, and 72.6% were homeless or unstably housed (Table 1). Ninety percent of participants had health insurance, most of which was public insurance.
Table 1.
Demographic characteristics by main drug used in the last three months among people who inject drugs, Public Health - Seattle and King County syringe services program clients, 2017–2019 (N=720)
| Main Drug Used, Last 3 Months | ||||
|---|---|---|---|---|
| Goofball N=120 # (%) | Heroin N=464 # (%) | Methamphetamine N=136 # (%) | p-value1 | |
| Age | <0.001 | |||
| 18-29 | 46 (38.3) | 131 (28.3) | 16 (11.8) | |
| 30-39 | 50 (41.7) | 178 (38.4) | 47 (34.6) | |
| 40-49 | 22 (18.3) | 86 (18.6) | 39 (28.7) | |
| 50+ | 2 (1.7) | 68 (14.7) | 34 (25.0) | |
| Gender | <0.0145 | |||
| Women (including transgender women) | 52 (43.3) | 163 (35.2) | 33 (24.4) | |
| Men (including transgender men) | 68 (56.7) | 298 (64.4) | 101 (74.8) | |
| Non-binary or other gender | 0 (0.0) | 2 (0.4) | 1 (0.7) | |
| Men who have sex with men2 | 8 (11.8) | 22 (7.4) | 46 (45.5) | <0.001 |
| Race / Ethnicity3 | ||||
| American Indian / Alaska Native | 14 (11.7) | 53 (11.4) | 17 (12.5) | 0.942 |
| Asian / South Asian | 5 (4.2) | 25 (5.4) | 5 (3.7) | 0.7445 |
| Black / African American | 4 (3.3) | 29 (6.3) | 12 (8.8) | 0.2095 |
| Hispanic / Latino | 9 (7.5) | 42 (9.1) | 10 (7.4) | 0.753 |
| Native Hawaiian / Pacific Islander | 3 (2.5) | 8 (1.7) | 4 (2.9) | 0.5985 |
| White | 94 (78.3) | 347 (74.8) | 106 (77.9) | 0.602 |
| Other | 5 (4.2) | 14 (3.0) | 5 (3.7) | 0.7525 |
| Homeless or unstably housed | 99 (82.5) | 333 (71.8) | 91 (66.9) | 0.016 |
| Has health insurance | 109 (90.8) | 412 (89.2) | 123 (90.4) | 0.825 |
| Public4 | 105 (87.5) | 369 (79.9) | 108 (79.4) | 0.142 |
| Private | 3 (2.5) | 44 (9.5) | 13 (9.6) | 0.0245 |
| Other | 1 (0.8) | 2 (0.4) | 3 (2.2) | 0.1115 |
| Incarcerated in last year | 68 (56.7) | 190 (41.0) | 39 (28.7) | <0.001 |
P-value is for a % test, unless otherwise indicated.
Among men and transgender men only (n=467).
Participants could select more than one race/ethnicity, so column percentages sum to more than 100%.
Includes Medicaid, Medicare, U.S. veterans health care benefits, Indian Health Service benefits.
P-value is for a Fisher’s exact test.
Age and gender were significantly different across groups defined by main drug, with the highest proportion of people age <30 years and women in the goofball group. The group whose main drug was goofball had the highest proportion of respondents who were homeless or unstably housed and incarcerated in the last year. On each of these demographic measures, participants whose main drug was goofball were more similar to those whose main drug was heroin than those whose main drug was methamphetamine. Men in the methamphetamine group were characterized by a higher proportion of MSM compared to the goofball and heroin groups.
Drug Use, Injection Behaviors, and Treatment
Participants whose main drug was goofball reported using goofball, heroin by itself, and methamphetamine by itself all for a median of 7 days per week (Table 2). The median number of days of weekly goofball use were lower among participants who reported either heroin (3 days) or methamphetamine (1 day) as their main drug.
Table 2.
Drug injection behaviors and treatment use and interest by main drug used in the last three months among people who inject drugs, Public Health - Seattle and King County syringe services program clients, 2017–2019 (N=720)
| Main Drug Used, Last 3 Months | ||||
|---|---|---|---|---|
| Goofball N=120 # (%) | Heroin N=464 # (%) | Methamphetamine N=136 # (%) | p-value1 | |
| Frequency of Drugs Used, Days Per Week 2 | ||||
| Goofball, median [IQR] | 7 [5–7] | 3 [1–7] | 1 [1–5] | <0.001 |
| Heroin by itself, median [IQR] | 7 [5–7] | 7 [7–7] | 2 [0–6] | <0.001 |
| Methamphetamine by itself, median [IQR] | 7 [4–7] | 4 [2–7] | 5.5 [2.5–7] | 0.010 |
| Drug Injection Behaviors | ||||
| Injects daily | 100 (83.3) | 364 (78.5) | 56 (41.2) | <0.001 |
| No. of injections per day, median [IQR] | 4 [3–5] | 3 [3–5] | 2 [2–3] | <0.0018 |
| Shared a syringe, last 3 mos. | 32 (26.7) | 84 (18.1) | 17 (12.5) | 0.013 |
| Shared other equipment3, last 3 mos. | 75 (63.0) | 234 (50.5) | 29 (21.3) | <0.001 |
| Inject alone | 91 (75.8) | 368 (79.5) | 108 (79.4) | 0.673 |
| Inject in public4 | 91 (75.8) | 306 (66.1) | 68 (50.0) | <0.001 |
| Injected in femoral vein, last 3 mos. | 23 (20.0) | 70 (15.3) | 6 (4.5) | 0.001 |
| Injected in jugular vein, last 3 mos. | 60 (51.7) | 169 (36.6) | 24 (18.1) | <0.001 |
| Years since first injection, median [IQR] | 9 [5–15] | 10 [5–19] | 11 [4–20] | 0.2358 |
| Drug Treatment Use and Interest | ||||
| Currently in any treatment for drug use5 | 30 (25.0) | 136 (29.4) | 30 (22.1) | 0.195 |
| Methadone | 13 (43.3) | 82 (60.3) | 9 (30.0) | 0.006 |
| Buprenorphine | 13 (43.3) | 42 (30.9) | 11 (36.7) | 0.397 |
| Naltrexone | 1 (3.3) | 0 (0.0) | 0 (0.0) | n/a |
| Other outpatient | 6 (20.0) | 27 (19.9) | 5 (16.7) | 0.9629 |
| 12-step / recovery group | 3 (14.3) | 6 (8.5) | 0 (0.0) | 0.5279 |
| Interest in reducing/stopping opioid use6 | 65 (73.9) | 267 (81.4) | 20 (42.6) | <0.001 |
| Interest in reducing/stopping stimulant use7 | 55 (61.8) | 181 (65.1) | 53 (50.5) | 0.032 |
Abbreviations: IQR, interquartile range (25th-75th); No., number; mos., months; SSP, syringe services program
P-value is for a χ2 test, unless otherwise indicated.
2019 data only (main drug goofball, n=79; main drug heroin, n=209; main drug methamphetamine, n=65).
Included cookers, cotton, water, or backloading.
Defined as “a park, alley, bathroom, car, or tent” in 2017 and “like a business, alley, public bathroom, or outside” in 2019.
Restricted to participants who reported current treatment for drug use (n=196). Participants could select more than one type of treatment.
Restricted to participants who reported any opioid use and no current treatment (n=463).
Restricted to participants who reported any stimulant use and no current treatment (n=472).
P-value is for Kruskal-Wallis rank test.
P-value is for a Fisher’s exact test.
Participants whose main drug was goofball had the highest frequency of reporting many injection risk behaviors than participants whose main drug was either heroin or methamphetamine. These behaviors included injecting every day, a higher number of injections per day, sharing a syringe, sharing other injection equipment, injecting in public, and injecting into their femoral or jugular vein.
One-quarter of participants whose main drug was goofball were currently in any treatment for drug use, which was similar to other participants. Methadone was the most common treatment among the heroin group, buprenorphine was most common in the methamphetamine group, and methadone and buprenorphine were evenly reported in the goofball group. Most opioid and stimulant users who were not in treatment were interested in reducing or stopping their use of each drug. Interest in reducing both opioid and stimulant use was highest among participants whose main drug was heroin.
Health Conditions and Overdose Experiences
Participants whose main drug was goofball had the highest prevalence of abscesses, infected blood clots or blood infection, and endocarditis, while participants whose main drug was methamphetamine had the lowest prevalence (Table 3). By contrast, participants whose main drug was methamphetamine had the highest frequency of reporting a bacterial sexually transmitted infection (STI) or HIV.
Participants whose main drug was goofball reported a similar frequency of experiencing an opioid overdose as those whose main drug was heroin, but there was a significant difference between groups regarding witnessing an opioid overdose with the goofball group reporting the highest level. Trends in naloxone possession followed a similar pattern, with more participants whose main drug was goofball reporting naloxone possession in the last 3 months and use in an overdose situation than other PWID participants. One-third of participants whose main drug was goofball reported experiencing a stimulant overdose or overamp in the last 12 months compared with 39.6% of the methamphetamine group and 23.5% of the heroin group. Witnessing a stimulant overdose/overamp in the last 12 months was reported most among participants whose main drug was goofball.
DISCUSSION AND CONCLUSIONS
Findings from these recent surveys of SSP clients in Seattle showed that goofball use is common, with over half of respondents reporting using heroin and methamphetamine together. Moreover, PWID whose main drug was goofball reported considerable health risks and morbidity, including more frequent injection, femoral and jugular vein injection, public injection, abscesses and skin infections, infected blood clots and blood infections, and endocarditis. They also reported more overdose-related risk including injecting alone and witnessing both opioid and stimulant overdoses. At the same time, the majority of PWID who reported that goofball was their main drug also reported interest in reducing or stopping their drug use. In light of the opioid crisis in the U.S., it is critical for stakeholders to recognize the substantial and growing overlap between opioid and methamphetamine use, acknowledge the contextual factors that may be driving the combined use of these drugs, and develop health interventions accordingly.
Polysubstance use is a global phenomenon, especially the use of opioids in combination with stimulants, and has been associated with high levels of HIV and other negative health outcomes.9–11 Prior opioid-stimulant co-use research has mostly focused on speedball. At present, there is limited epidemiologic data on the unique health effects of combined heroin and methamphetamine use. Due to the shorter half-life of heroin relative to methamphetamine,12 people using goofball may re-dose when the effects of heroin wane but before the effects of methamphetamine have worn off, potentially leading to the unsafe injection behaviors or overdose.
A very high proportion (82.5%) of people whose main drug was goofball were homeless or unstably housed. This aligns with dramatic increases in homelessness in the Seattle area.13 Many other observed associations with goofball use are correlated with homelessness. People living outdoors may use stimulants to counter the depressant effects of opioids to remain more aware of their possessions and surroundings.14 However, further research is needed to better understand the motivations and causes of the increase in methamphetamine use, particularly among this largely homeless population with high levels of risk and vulnerability.
Although methamphetamine use has been well-documented among MSM and is a risk factor for HIV/STI acquisition,15,16 very few MSM reported that goofball was their main drug. This helps explain the finding of a higher prevalence of HIV and STI in the methamphetamine group. However, people whose main drug was goofball were the most likely to report sharing a syringe or other injection equipment. This is of particular concern given the high HIV prevalence among MSM who inject methamphetamine in Seattle and the potential for connecting high and low prevalence populations.2,17
Injecting into the jugular vein was reported by over one-half of people whose main drug was goofball. Jugular vein injection can lead to serious sequelae including deep soft tissue infections,18 internal jugular vein thrombosis (Lemierre’s syndrome) and septic thrombophlebitis,19 pneumothorax,20 and vocal cord paralysis.21 Injecting into central veins may be more expected among older PWID who have difficulty injecting into peripheral veins due to scar tissue, but we observed that PWID who use goofball were the youngest group and correspondingly had the shortest period of time since first injection. Another hypothesis is people who inject into the jugular vein have a higher tolerance and seek a faster onset of drug effects. There are limited published data on recent trends in jugular vein injection so it is unclear if this is a local or more widespread phenomenon.22–24
The majority of participants reported interest in reducing both their opioid and stimulant use. Medications to treat opioid use disorder are highly effective.25,26 The efficacy of treatments for stimulant use disorder – including cognitive behavioral therapy, contingency management, and pharmacological treatment with mirtazapine – have been more modest.27–30 Even in the context of high levels of health insurance coverage (i.e., Washington is a Medicaid-expansion state), only a minority of PWID whose main drug was goofball reported any current treatment. The availability of low-barrier buprenorphine treatment in King County has expanded in recent years, including at the SSP where this survey was conducted.31 The low rate of treatment in this sample is consistent with previous local findings32 and may be due, in part, to the real or perceived treatment eligibility requirements, stigma, dislike of available medications, or challenges related to unstable housing. The high proportion of opioid users who also use methamphetamine presents a challenge to treatment for opioid use disorder. Research has evaluated the effects of stimulant use on both methadone and buprenorphine treatment and found that treatment retention was lower among patients using stimulants.33,34 More research is needed on effective treatments for stimulant use disorder as well as co-occurring opioid and stimulant use disorders.
In the Seattle area, the increase in methamphetamine use has paralleled an increase in methamphetamine-involved deaths, many of which also involved opioids.35 Although we did not find that people who primarily use goofball were more likely than others to experience an opioid overdose or stimulant overdose/overamp, several behaviors associated with overdose were higher in this group including more frequent injection and injecting alone. Moreover, people who primarily use goofball were the most likely to witness opioid and stimulant overdoses, highlighting the critical importance of engaging this group in overdose prevention services. Fortunately, naloxone possession was also highest in this group, suggesting that these efforts have been successful.
This analysis has several limitations. First, while this survey attempted to get a representative sample of SSP clients in Seattle, it is not generalizable to all PWID. Second, the survey was designed to be brief and facilitate program evaluation, so it did not include detailed questions about trajectories and motivations for goofball use. Third, individuals may have completed the survey in both years, which would have resulted in an inflated sample size and standard error, but this could not be measured. Fourth, the analysis included multiple potential correlates of goofball use and did not adjust for multiple comparisons. It is possible that some associations were observed by chance alone. Related to this, there was likely collinearity across some factors, which was not accounted for in the bivariate analyses. Fifth, this survey sampled PWID thus most participants reported injecting goofball as opposed to smoking. The related risks and motivations among people who inject goofball may be different than those who primarily smoke goofball. Finally, this cross-sectional study cannot disentangle the direction of the association between goofball use and its correlates. Prospective studies are needed to determine if PWID who engage in higher risk behaviors are more likely to use goofball, or if goofball use is a factor in increasing risk behaviors among PWID.
SCIENTIFIC SIGNIFICANCE
The high prevalence of goofball use, particularly among younger PWID and those situated in high-risk environments, points to the critical need to identify and tailor harm reduction and other prevention services to this population. The effectiveness of interventions related to the opioid crisis in the U.S. – including the expansion of access to medications for opioid use disorder, naloxone distribution, and SSPs – may be diminished without consideration of the co-use of methamphetamine among many PWID. Moreover, these efforts must consider the profoundly high rates of homelessness among PWID and the intersecting impacts of housing instability on substance use and related morbidities. Continued development and implementation at scale of multifaceted, evidence-based interventions for methamphetamine and heroin co-use has the potential to improve the health and lives of a significant number of PWID.
ACKNOWLEDGEMENTS
This survey was conducted as part of routine surveillance activities by the Public Health – Seattle & King County (PHSKC) HIV/STD Program. Research reported in this publication was supported by the University of Washington / Fred Hutch Center for AIDS Research, an NIH-funded program under award number AI027757 which is supported by the following NIH Institutes and Centers: NIAID, NCI, NIMH, NIDA, NICHD, NHLBI, NIA, NIGMS, NIDDK. REDCap at the University of Washington’s Institute of Translational Health Science is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1 TR002319.
The authors thank the following PHSKC staff for conducting the participant interviews: Angelina Benson, Trevor Evans, Noah Frank, Malin Hamblin, Karen Hartfield, Abby Ketchum, Kevin Kogin, Mel LaBelle III, Thea Oliphant-Wells, Rachel Patrick, Emanuel Rodriguez, Shonita Savage, and Holly Whitney. The authors also thank Alexa Juarez for her assistance preparing the manuscript. We are especially grateful to the participants for sharing their time and stories with us.
DECLARATION OF INTEREST
MRG has received research support from Hologic. SNG, KSK, and JT report no conflicts of interest. The authors alone are responsible for the content and writing of this paper.
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