Abstract
Background:
Methamphetamine use is prevalent among sexual and gender minority (SGM) populations and is associated with increased risk for HIV acquisition. Studies are needed to examine the prevalence of intravenous methamphetamine use and explore its association with HIV status and PrEP uptake.
Methods:
Between August 2022 – July 2023, 29,880 SGM people who have sex with men in the U.S. aged 16 and over completed a screening survey for a cohort study on methamphetamine use and HIV prevention. The survey captured socio-demographic characteristics, methamphetamine use (any and injection) and other substance use, and HIV-related measures (including current and previous PrEP use).
Results:
The median age was 34 years and 49.7% were persons of color. Overall, 35.0% reported methamphetamine use; of whom 45.1% had injected it in the prior 12 months. Compared to people with non-injection methamphetamine use, respondents who injected methamphetamine were more likely to be older, white (vs. non-Hispanic Black or Hispanic), living with HIV or not know their status (vs. HIV-negative), to have injected cocaine, and to have had a sexual encounter without consent under the influence of alcohol/drugs. Among those who were HIV-negative, people who injected methamphetamine were less likely to currently take PrEP and more likely to have discontinued PrEP compared to those who reported non-injection methamphetamine use.
Conclusion:
Expanded efforts are needed to develop and implement targeted interventions, including PrEP and harm reduction approaches for SGM people who inject methamphetamine, to reduce risk of HIV and other infectious diseases, as well as other injection-related harms.
Keywords: Methamphetamine, intravenous drug use, sexual assault, sexual and gender minorities
1. INTRODUCTION
Methamphetamine is a highly addictive central nervous system stimulant that can be smoked, snorted, swallowed, administered rectally (“booty bump”), or injected intravenously (1). Although its use has received less attention than the opioid epidemic in recent years, methamphetamine poses a major problem in the United States (U.S.), with an estimated 16.8 million people reporting use at least once in their lifetime and 2.5 million people reporting use in the last 12 months (2). Interrelated factors associated with methamphetamine use include lower educational level, lower income, lack of health insurance, housing instability, carceral system involvement, and polysubstance use (3, 4). Methamphetamine use has a myriad of short and long-term health consequences, including dental problems, memory loss, paranoia, cardiovascular strain, and increased risk of acquiring HIV and hepatitis C (HCV) (1, 2), and methamphetamine-involved overdose deaths have risen sharply in recent years, nearly tripling between 2015 and 2019 (5).
Intravenous (IV) methamphetamine use carries heightened risks compared to other routes of administration, due to harms associated with injection itself—such as transmission of HIV, HCV, and bacterial infections through syringe sharing—and its more frequent, intense, and dependent use patterns (6-10). In a multicity U.S. study, methamphetamine was the primary substance reported by a third of people who inject drugs (PWID), with significant regional variation (11). Rates of methamphetamine injection are disproportionately high among sexual minority men, especially in the context of ‘chemsex’ and ‘party and play (PnP, parTy),’ which involves methamphetamine use during sexual activity, and ‘slamsex,’ which involves injection of substances, including methamphetamine, during sexual activity (6, 9, 11-25). Prevalence estimates of slamsex among men who have sex with men vary widely, with reports ranging from 2% to 91%, highlighting stark variation by context and population (26).
Among sexual minority men, research has demonstrated a clear association between methamphetamine use and HIV transmission (27-34), with growing attention to injection as a particularly high-risk modality (11, 12, 34, 35). Notably, the multicity U.S. study previously mentioned of nearly 1000 MSM who inject drugs found that HIV prevalence was almost 50% higher among those who primarily injected methamphetamine (38% of the total sample) than those who primarily injected other drugs (11). While sexual minority men who inject methamphetamine report lower likelihood of sharing syringes, they may have less knowledge regarding safe injection practices and a higher frequency of being injected by peers (36). Additionally, although sexual minority men who use methamphetamine (by any route) are more likely to report using PrEP, they often have lower PrEP adherence and retention in PrEP care (37-41); there is very limited evidence examining these trends among sexual minority men who specifically inject methamphetamine, despite their elevated HIV risk. Methamphetamine use thus exacerbates bio-behavioral consequences across the HIV care continuum, including “poor continuation in care, low adherence to HIV medication and subsequently poor clinical outcomes, including high viral load (or lack of viral suppression)…and other comorbid conditions leading to higher mortality rates (p. S471)” (34). These patterns are shaped by intersecting forms of social and economic marginalization that restrict access to healthcare, support systems, and safe spaces.
Greater clarity is needed regarding the correlates of IV methamphetamine use to guide the implementation of harm reduction interventions and PrEP implementation efforts that are designed to meet the needs of this population. To address this gap, this paper examines the associations between injection and non-injection methamphetamine use and socio-demographic characteristics, substance use, HIV status, and PrEP uptake in a large U.S. national sample of sexual and gender minority men who have sex with men.
2. METHODS
2.1. Human Subjects
The study was approved by the Institutional Review Board (IRB) of CUNY and a waiver of parental consent was obtained for participants aged 16 and 17.
2.2. Study Design and Setting
The present analysis was conducted using screening data from the American Transformative HIV Study (AMETHST): a U.S. national longitudinal cohort study for cisgender men who have sex with men and transgender persons who have sex with men. Study recruitment was completed between August 2022 – July 2023 via advertisements (ads) on online geospatial social networking applications (apps) used by this population. These targeted ads indicated that the purpose of the enrolling/screening was for a compensated study; however, no compensation was provided for completing the online screening survey. A total of 55 ads were used across multiple platforms, with some ads utilizing imagery and text specifically designed to oversample for individuals who use methamphetamine (e.g., the appearance of smoke and use of the word “parTy”). In total, our ads generated 29,880 completed surveys from eligible participants. Eligibility criteria for the screening survey included being over the age of 16 and living in the U.S. or its territories. Participants who identified as cisgender women were excluded from the dataset.
2.3. Data Collection and Measures
Sociodemographic characteristics.
Participants self-reported their age in years (continuous), race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Other Multiracial), gender (cisgender man, transgender man, transgender woman, something else), sex assigned at birth (male, female), and sexual orientation (gay/homosexual, bisexual, something else).
Substance use-related measures.
Participants were asked to report how many days they used methamphetamine as well as cocaine in the previous 3 months (I have not used in the last three months, 1-5 days, 6-10 days, 11-20 days, 21-30 days, 31 days or more). Each of these variables were dichotomized into any use vs. no use in the prior three months. Participants also reported whether they had injected any drugs recreationally in the previous 12 months (yes/no). If participants responded “yes,” further questions regarding type of substance (methamphetamine, cocaine, opioids, ketamine, or other) were asked. Participants were then categorized into injection methamphetamine use in the prior 12 months, non-injection methamphetamine use in the prior 3 months, and no methamphetamine use in the prior 3 months.
HIV-related measures.
Participants were asked to report their HIV status (negative, positive, don’t know) and when they were diagnosed (less than 1 year ago, 1-5 years, more than 5 years) for those who reported HIV-positive status. For those who reported an HIV-negative or unknown status, they were asked about their PrEP status (I don’t know what PrEP is, I have never taken PrEP, I am currently taking PrEP, taken PrEP before but not taking it currently). PrEP status was further categorized into never taken PrEP, currently taking PrEP, or discontinued PrEP use. The number of condomless receptive anal acts in the previous 6 months (continuous) and whether the participant had a nonconsensual sexual encounter under the influence of drugs and/or alcohol in the previous 5 years (yes/no) were assessed.
2.4. Statistical analysis
Descriptive statistics were reported using frequencies and percentages for categorical variables and medians and interquartile range (IQR) for continuous variables for the entire sample. Next, we assessed the differences in demographic, substance use, and HIV-related measures between those who reported injection methamphetamine use, non-injection methamphetamine use, and no methamphetamine use. We used chi-squared tests to compare categorical variables and Wilcoxon rank-sum tests for continuous variables. Finally, we built two multinomial logistic regression models to examine the association between demographic, substance use, and HIV-related measures (HIV status and PrEP status) and methamphetamine use group (injection methamphetamine use, non-injection methamphetamine use, no methamphetamine use). Our first model included self-reported HIV status (positive, negative, unknown) to examine the relationship between HIV status and methamphetamine use group. In our second model, we excluded all participants who reported an HIV positive status to examine the relationship between PrEP usage and methamphetamine use group as those who reported living with HIV were excluded from the PrEP status question (n=25,273). Variables included in both models were: age, race/ethnicity, gender, forced sexual encounter and cocaine use—these variables were selected based on their known risk for HIV in the literature (42-46). Adjusted odds ratios (aOR) and corresponding 95% confidence intervals (CI) were reported for both models. All analyses were conducted using SAS software, Version 9.4 (SAS Institute Inc., Cary, NC, USA). Given the large sample size in our study, we set a more stringent significance level of 0.001 for our bivariate analyses to reduce the risk of Type I errors.
3. RESULTS
As noted, 29,880 completed surveys from eligible participants were recorded. The median age was 34 years old (IQR = 28-43). Half (50.3%) identified as non-Hispanic White, 14.5% identified as non-Hispanic Black, 23% identified as Hispanic and 12.3% identified as multiracial. Most (83.6%) identified as cisgender male, 1.4% identified as a transgender man, 2.9% identified as a transgender woman and 12.1% identified as something else (e.g., non-binary). The majority (66.3%) identified as gay, 20.7% as bisexual and 13.0% as something else (Table 1). More than one-third (35.0%) of the sample reported methamphetamine use in the previous 3 months with 45.1% of these participants reporting IV use in the previous 12 months.
Table 1.
Socio-demographic characteristics among participants completing the AMETHST screening survey (n = 29,880), 2022-2023.
| Characteristic | Total Sample (N=29,880) |
|---|---|
| Age (median, IQR) | 34.0 (28.0-43.0) |
| Race/Ethnicity (n,%) | |
| Non-Hispanic White | 15015 (50.3) |
| Non-Hispanic Black | 4326 (14.5) |
| Hispanic | 6878 (23.0) |
| Other Multiracial | 3661 (12.3) |
| Gender (n,%) | |
| Cis man | 24969 (83.6) |
| Trans man | 429 (1.4) |
| Trans woman | 877 (2.9) |
| Something else | 3605 (12.1) |
| Sex at Birth (n,%) | |
| Male | 29373 (98.3) |
| Female | 507 (1.7) |
| Sexual Orientation (n,%) | |
| Gay/homosexual | 19818 (66.3) |
| Bisexual | 6173 (20.7) |
| Something else | 3889 (13.0) |
| Methamphetamine use group (n, %) | |
| IV-methamphetamine use | 4706 (15.8) |
| Non-IV methamphetamine use | 5740 (19.2) |
| No methamphetamine use | 19434 (65.0) |
| HIV Status (n, %) | |
| Positive | 4607 (15.4) |
| Negative | 20210 (67.6) |
| Unknown | 5063 (16.9) |
IV: Intravenous
Table 2 shows bivariate differences between those who reported IV methamphetamine use (n=4,707), non-IV methamphetamine use (n=5,740) and no methamphetamine use (n=19,434) across sociodemographic, other substance use, and HIV-related measures. All findings were statistically significant. As a result, and in the interest of parsimony, we focus more on our multinomial regression models—described in the following paragraphs.
Table 2.
Demographic, substance use, and HIV status differences between SMM reporting injection methamphetamine use, non-injection methamphetamine use, and no methamphetamine use, AMETHST screening survey, 2022-2023.
| Characteristic | IV Meth Use (n=4,706) |
Non-IV Meth use (n=5,740) |
No Meth Use (n=19,434) |
χ2 | Cramer’s V | p-value |
|---|---|---|---|---|---|---|
| Age (median, IQR) | 38 (32-46) | 37 (31-45) | 33 (26-42) | --- | --- | <0.001 |
| Race/Ethnicity (n,%) | 166.9 | 0.053 | <0.001 | |||
| Non-Hispanic White | 2685 (57.1) | 2746 (47.8) | 9584 (49.3) | |||
| Non-Hispanic Black | 559 (11.9) | 955 (16.6) | 2812 (14.5) | |||
| Hispanic | 836 (17.8) | 1345 (23.4) | 4697 (24.2) | |||
| Other Multiracial | 626 (13.3) | 694 (12.1) | 2341 (12.1) | |||
| Gender (n,%) | 171.3 | 0.054 | <0.001 | |||
| Cis man | 3928 (83.5) | 4639 (80.8) | 16402 (84.4) | |||
| Trans man | 26 (0.6) | 49 (0.9) | 354 (1.8) | |||
| Trans woman | 167 (3.6) | 263 (4.6) | 447 (2.3) | |||
| Something else | 585 (12.4) | 789 (13.8) | 2231 (11.5) | |||
| HIV Status (self-report) (n,%) | 3405.5 | 0.239 | <0.001 | |||
| Negative | 2045 (43.5) | 3195 (55.7) | 14970 (77.0) | |||
| Positive | 1707 (36.3) | 1484 (25.9) | 1416 (7.3) | |||
| Don’t know | 954 (20.3) | 1061 (18.5) | 3048 (15.7) | |||
| When Diagnoseda (n=4607) (n,%) | 34.9 | 0.062 | <0.001 | |||
| Less than 1 year ago | 143 (8.4) | 156 (10.5) | 200 (14.1) | |||
| 1-5 years | 525 (30.8) | 491 (33.1) | 470 (33.2) | |||
| More than 5 years | 1039 (60.9) | 837 (56.4) | 746 (52.7) | |||
| PrEP Statusb (n=25273) (n,%) | 262.7 | 0.072 | <0.001 | |||
| Never taken PrEP | 1801 (60.1) | 2615 (61.4) | 10044 (55.7) | |||
| Currently taking PrEP | 447 (14.9) | 796 (18.7) | 4659 (25.9) | |||
| Discontinued PrEP use | 751 (25.0) | 845 (19.9) | 3315 (18.4) | |||
| Condomless receptive anal acts in previous 6 months (median, IQR) | 6 (2-20) | 4 (1-10) | 2 (0-5) | --- | --- | <0.001 |
| Sexual encounter, no consent, under influence of drugs/alcohol (n,%) | 1860.8 | 0.250 | <0.001 | |||
| Yes | 1707 (36.3) | 1594 (27.7) | 2304 (11.9) | |||
| No | 2999 (63.7) | 4146 (72.3) | 17130 (88.1) | |||
| Days of methamphetamine use in previous 3 month (n,%) | --- | --- | <0.001 | |||
| 1-5 days | 388 (8.2) | 1499 (26.1) | --- | |||
| 6-10 days | 303 (6.4) | 641 (11.2) | --- | |||
| 11-20 days | 441 (9.4) | 620 (10.8) | --- | |||
| 21-30 days | 480 (10.2) | 529 (9.2) | --- | |||
| 31 or more days | 2981 (63.3) | 2451 (42.7) | --- | |||
| Cocaine in previous 3 months (n,%) | 2561.1 | 0.293 | <0.001 | |||
| Yes | 1586 (33.7) | 1735 (30.2) | 1727 (8.9) | |||
| No | 3120 (66.3) | 4005 (69.8) | 17707 (91.1) | |||
| Type of injection drug use in previous 12 months (n,%) | ||||||
| Opioid | 552 (11.7) | 0 (0.0) | 88 (0.5) | 2416.2 | 0.284 | <0.001 |
| Cocaine | 492 (10.4) | 0 (0.0) | 52 (0.3) | 2304.1 | 0.278 | <0.001 |
| Ketamine | 422 (8.9) | 0 (0.0) | 26 (0.1) | 2094.5 | 0.265 | <0.001 |
Question was only asked to participants who reported a positive HIV status
Question was only asked if a participant reported a negative or unknown HIV status
Cocaine in previous 3 months did not distinguish between route of administration
IV: Intravenous
Results of the self-reported HIV status and PrEP status models are reported in Tables 3 and 4, respectively. Compared to those reporting no methamphetamine use, those who reported IV methamphetamine use had significantly lower odds of being non-Hispanic Black (aOR=0.57, 95% CI: 0.51, 0.64), Hispanic (aOR=0.60, 95% CI: 0.55, 0.66), and a transgender man (aOR=0.40, 95% CI: 0.26, 0.61). In addition, those reporting IV methamphetamine use had significantly higher odds of being a transgender woman (aOR=1.37, 95% CI: 1.12, 1.68), self-report HIV positive status (aOR=8.74, 95% CI: 7.98-9.56), self-report unaware of their HIV status (aOR=2.31, 95% CI: 2.10-2.53), having a nonconsensual sexual encounter under the influence of drugs/alcohol (aOR=3.81, 95% CI: 3.50-4.14) and cocaine use in the previous 3 months (aOR=4.80, 95% CI: 4.40-5.23) compared to those reporting no methamphetamine use.
Table 3.
Multivariable multinomial logistic regression results for the total sample (N=29,880), AMETHST screening survey, 2022-2023
| IV Meth Use vs. No Meth Use |
Non-IV Meth Use vs. No Meth Use |
IV Meth Use vs. Non-IV Meth Use |
||||
|---|---|---|---|---|---|---|
| Characteristic | aOR | 95% CI | aOR | 95% CI | aOR | 95% CI |
| Age | 1.04 | 1.03-1.04 | 1.03 | 1.03-1.04 | 1.004 | 1.001-1.008 |
| Race/Ethnicity | ||||||
| Non-Hispanic White | REF | REF | REF | REF | REF | REF |
| Non-Hispanic Black | 0.57 | 0.51-0.64 | 1.07 | 0.97-1.18 | 0.53 | 0.47-0.60 |
| Hispanic | 0.60 | 0.55-0.66 | 1.01 | 0.93-1.09 | 0.60 | 0.54-0.66 |
| Other Multiracial | 0.98 | 0.87-1.09 | 1.08 | 0.97-1.19 | 0.91 | 0.80-1.02 |
| Gender | ||||||
| Cis man | REF | REF | REF | REF | REF | REF |
| Trans man | 0.40 | 0.26-0.61 | 0.61 | 0.45-0.84 | 0.65 | 0.40-1.06 |
| Trans woman | 1.37 | 1.12-1.68 | 1.80 | 1.52-2.14 | 0.76 | 0.62-0.93 |
| Something else | 1.03 | 0.92-1.15 | 1.18 | 1.08-1.30 | 0.87 | 0.78-0.98 |
| HIV Status (self-report) | ||||||
| Negative | REF | REF | REF | REF | REF | REF |
| Positive | 8.74 | 7.98-9.56 | 4.52 | 4.15-4.93 | 1.93 | 1.76-2.12 |
| Don’t know | 2.31 | 2.10-2.53 | 1.63 | 1.49-1.77 | 1.42 | 1.28-1.58 |
| Sexual encounter, no consent, under influence of drugs/alcohol | ||||||
| Yes | 3.81 | 3.50-4.14 | 2.55 | 2.36-2.76 | 1.49 | 1.37-1.63 |
| No | REF | REF | REF | REF | REF | REF |
| Cocaine in previous 3 months | ||||||
| Yes | 4.80 | 4.40-5.23 | 4.14 | 3.82-4.48 | 1.16 | 1.07-1.26 |
| No | REF | REF | REF | REF | REF | REF |
Cocaine in previous 3 months did not distinguish between route of administration
Note. Bolded is significant at p<0.05
IV: Intravenous
Table 4.
Multivariable multinomial logistic regression results for the sample reporting negative or unknown HIV status (N=25,273), AMETHST screening survey, 2022-2023
| IV Meth Use vs. No Meth Use |
Non-IV Meth Use vs. No Meth Use |
IV Meth Use vs. Non-IV Meth Use |
||||
|---|---|---|---|---|---|---|
| Characteristic | aOR | 95% CI | aOR | 95% CI | aOR | 95% CI |
| Age | 1.04 | 1.03-1.04 | 1.04 | 1.03-1.04 | 1.004 | 1.000-1.009 |
| Race/Ethnicity | ||||||
| Non-Hispanic White | REF | REF | REF | REF | REF | REF |
| Non-Hispanic Black | 0.72 | 0.63-0.83 | 1.15 | 1.03-1.28 | 0.63 | 0.54-0.74 |
| Hispanic | 0.65 | 0.58-0.73 | 1.08 | 0.98-1.18 | 0.60 | 0.53-0.69 |
| Other Multiracial | 1.07 | 0.95-1.22 | 1.14 | 1.02-1.28 | 0.94 | 0.81-1.09 |
| Gender | ||||||
| Cis man | REF | REF | REF | REF | REF | REF |
| Trans man | 0.40 | 0.26-0.63 | 0.60 | 0.43-0.83 | 0.67 | 0.40-1.12 |
| Trans woman | 1.66 | 1.33-2.08 | 1.81 | 1.49-2.19 | 0.92 | 0.73-1.16 |
| Something else | 1.10 | 0.97-1.24 | 1.24 | 1.11-1.37 | 0.89 | 0.77-1.02 |
| PrEP Status | ||||||
| Never taken PrEP | REF | REF | REF | REF | REF | REF |
| Currently taking PrEP | 0.49 | 0.43-0.55 | 0.61 | 0.56-0.67 | 0.79 | 0.69-0.90 |
| Discontinued PrEP | 1.19 | 1.08-1.32 | 0.94 | 0.86-1.03 | 1.27 | 1.13-1.43 |
| Sexual encounter, no consent, under influence of drugs/alcohol | ||||||
| Yes | 3.94 | 3.59-4.34 | 2.64 | 2.41-2.88 | 1.50 | 1.35-1.66 |
| No | REF | REF | REF | REF | REF | REF |
| Cocaine in previous 3 months | ||||||
| Yes | 5.38 | 4.89-5.93 | 4.46 | 4.09-4.86 | 1.21 | 1.09-1.34 |
| No | REF | REF | REF | REF | REF | REF |
Cocaine in previous 3 months did not distinguish between route of administration
Note. Bolded is significant at p<0.05
IV: Intravenous
Compared to those reporting no methamphetamine use, those who reported non-IV methamphetamine use had significantly lower odds of reporting transgender male gender (aOR=0.61, 95% CI: 0.45-0.84). Furthermore, those reporting non-IV methamphetamine use had significantly higher odds of reporting transgender woman gender (aOR=1.80, 95% CI: 1.52-2.14), reporting another gender other than cis/trans male or female (aOR=1.18, 95% CI: 1.08-1.30), self-reporting HIV positive (aOR=4.52, 95% CI: 4.15-4.93), self-reporting unknown HIV status (aOR=1.63, 95% CI: 1.49-1.77), having a nonconsensual sexual encounter under the influence of drugs/alcohol (aOR=2.55, 95% CI: 2.36-2.76) and cocaine use in the previous 3 months (aOR=4.14, 95% CI: 3.82-4.48) compared to those reporting no methamphetamine use.
Finally, compared to those reporting non-IV methamphetamine use, those reporting IV methamphetamine use had significantly lower odds of being non-Hispanic Black (aOR=0.53, 95% CI: 0.47-0.60), Hispanic (aOR=0.60, 95% CI: 0.54-0.66), reporting transgender woman gender (aOR=0.76, 95% CI: 0.62-0.93) and reporting another gender other than cis/trans male or female (aOR=0.87, 95% CI: 0.78-0.98). In addition, those who reported IV methamphetamine use had significantly higher odds of reporting HIV positive (aOR=1.93, 95% CI: 1.76-2.12), unknown HIV status (aOR=1.42, 95% CI: 1.28-1.58), having a nonconsensual sexual encounter under the influence of drugs/alcohol (aOR=1.49, 95% CI: 1.37-1.63) and injection cocaine use in the previous 3 months (aOR=1.16, 95% CI: 1.07-1.26) compared to those reporting non-IV methamphetamine use.
In our adjusted model examining PrEP status among people with HIV negative or unknown status (n=25,273), we found similar significant associations between socio-demographic and substance use measures as the HIV status model (Table 4). Compared to those reporting no methamphetamine use, those reporting IV methamphetamine use had significantly lower odds of currently taking PrEP (aOR=0.49, 95% CI: 0.43-0.55) and significantly higher odds of discontinuing PrEP (aOR=1.19, 95% CI: 1.08-1.32). Compared to those who report no methamphetamine use, those who report non-IV methamphetamine use had significantly lower odds of currently taking PrEP (aOR=0.61, 95% CI: 0.56-0.67). Finally, compared to those who report non-IV methamphetamine use, those who report IV methamphetamine use had significantly lower odds of currently taking PrEP (aOR=0.79, 95% CI: 0.69-0.90) and significantly higher odds of discontinuing PrEP (aOR=1.27, 95% CI: 1.13-1.43).
4. DISCUSSION
In this study of nearly thirty thousand responses from sexual and gender minority individuals on geosocial networking apps, almost half (45.1%) of those who reported methamphetamine use said they had injected it in the past year. This is consistent with prior studies highlighting the growing prevalence of methamphetamine injection among sexual minority men, particularly in urban centers (4, 11, 34). In addition, we found that those who reported IV methamphetamine use were less likely to be currently on PrEP and more likely to have discontinued PrEP compared to both non-IV methamphetamine users and those without recent methamphetamine use. These data reiterate the need to design, implement, and evaluate interventions targeting adherence to biomedical HIV prevention interventions (such as PrEP) and harm reduction interventions (such as syringe services programs) for those who inject methamphetamine.
The last few years have seen renewed focus on the risk methamphetamine poses for sexual and gender minority populations, particularly regarding HIV (32, 37). Much of this work has focused on categorizing differences between those who use methamphetamine and those who do not (regardless of route of administration). Consistent with the literature, we also found that those who do not use methamphetamine differ from those who do in meaningful ways—thus, we do not belabor them here. Meanwhile, there has been less published on the comparison between those who inject methamphetamine and those who use it through other routes of administration, as injection has been associated with heightened risk of acute and longer term adverse outcomes including infections and substance dependency. We found that people who inject methamphetamine are more likely than those who use it without injecting to be older, white (vs. Black, or Latinx), and HIV-positive or not know their status (compared to HIV-negative). This demographic profile is consistent with prior research showing that White sexual minority men are disproportionately represented among those who inject methamphetamine (9, 47, 48), and that people who inject methamphetamine have higher rates of HIV compared to those who use it by other means (34). IV methamphetamine use was also associated with worse outcomes even when compared to other people who use methamphetamine (but do not inject) in ways that may warrant targeted interventions. Specifically, they were more likely to have used cocaine recently and were more likely to have had a sexual encounter that they did not consent to under the influence of alcohol or drugs. This finding underscores the importance of both primary and secondary sexual assault prevention among gender and sexual minorities, an area for future intervention and implementation research.
The literature suggests that most people are not introduced to methamphetamine by injecting it, but rather move to injection after a period of using it via other methods in order to experience a more intense high (49). Thus, individuals who inject methamphetamine may have likely been using it longer than those who use it without injecting, although we lack data to confirm this, indicating an area for further investigation. Our data suggest that those who report injecting methamphetamine use it more frequently, as evidenced by the number of days of use in the previous 3 months. However, we did not capture details about the route of administration or the amount of methamphetamine used in the previous 3 months, which would provide additional insights into patterns of use.
Finally, we highlight our findings regarding PrEP use among HIV-negative and persons who did not know their HIV status. We observed lower rates of current PrEP use among both those using methamphetamine by injection and non-injection, compared to those not using methamphetamine. Even more concerning is the finding that those reporting injection methamphetamine use had lower odds of current PrEP use compared to those engaged in non-injection methamphetamine use. Given the heightened risk of HIV transmission associated with methamphetamine use, one would ideally expect to see equal or higher rates of PrEP use among these individuals. Our findings add to the growing literature suggesting that injection methamphetamine use is a key marker for both HIV vulnerability and reduced access to biomedical prevention , and underscore the need for targeted and enhanced interventions to increase PrEP care engagement and retention among people who use methamphetamine, particularly those injecting methamphetamine. Current systems, such as standard clinical models of PrEP delivery, typically rely on individuals to proactively seek services and remain engaged in care; however, methamphetamine use has been associated with numerous barriers to care engagement, including unstable housing, co-occuring mental health conditions, and stigma from healthcare providers (3, 37). Emerging care models, such as those that involve peer navigation, mobile clinics, and contingency management, have shown promise in improving health outcomes among populations facing similar barriers and could be tailored to the needs and preferences of people who inject methamphetamine. Likewise, new formulations of PrEP, such as long-acting injectables, may be more effective regimens for people who use methamphetamine.
4.1. Limitations
Our findings should be understood considering their limitations. Data were taken from a survey being used to screen individuals for an incentivized research study (although the screening survey itself had no incentive attached to it). Although we were not permitted by apps to name methamphetamine directly in our ads, some ads featured imagery/text (such as the word “parTy”) in ways to suggest we wanted to enroll people who use methamphetamine. Thus, the fact that greater than one-third of our responses were people who reported methamphetamine use should not be interpreted as a prevalence estimate. Furthermore, many ads mentioned that the study involved at-home HIV testing. Individuals not interested in participating in a longitudinal study or one with these features (e.g., taking an at-home HIV test) would be less likely to take the screener. Although we used a range of geosocial sexual networking apps for recruitment, not all SGM individuals use these apps. Thus, our sample is not meant to be representative. We also note that our measure of race and ethnicity did not capture the full range of options currently being used by the U.S. census.
During an individual ad campaign, our ad was displayed once to a participant when they logged into the app. If they chose to complete the survey, they would be permitted one entry (duplicate attempts during a single ad campaign were blocked, and once an ad campaign ended the unique URL to get into the study was deactivated). However, it is possible that a participant could respond a second time when a new ad campaign was launched. At the end of the screening survey, all participants were asked to provide contact information regardless of their eligibility for the AMETHST study. In instances in which participants volunteered their contact information, we were able to detect duplication, and those responses were removed from the screener survey data used in this manuscript.
Next, participants were asked if they had used methamphetamine in the past 3 months and separately asked if they had injected methamphetamine in the prior 12 months. Had we used a 12-month recall window for non-IV methamphetamine use, we likely would have seen even higher reported rates of use. However, the misalignment in recall periods may have biased our results. The rationale for using a recall window of three months was to screen for recent use as a matter of enrollment criteria for the AMETHST study. Additionally, given the brief nature of our survey, we were unable to ask about other specific routes of administration (e.g., smoking, snorting, “booty bump”) and it is likely participants have used methamphetamine via other routes. In addition, we were unable to capture other potential confounders, such as mental health status, geographical location and access to healthcare services. We also did not ask about reuse or sharing of needles or awareness/use of syringe exchange programs. These would be important areas for further investigation as each likely poses unique health risks (e.g., damage to the teeth, lungs, or the rectum) and exposure to bloodborne pathogens.
5. CONCLUSIONS
In this study, among those using methamphetamine, we identified both high rates of IV methamphetamine use in addition to suboptimal rates of PrEP use. Our findings highlight the urgent need to scale up interventions to address injection methamphetamine use among sexual and gender minority individuals, including access to evidence-based harm reduction strategies and the need for targeted implementation strategies for PrEP implementation among those who use methamphetamine, especially through injection.
ACKNOWLEDGEMENTS
Special thanks to Matthew Stief, and other members of the AMETHST team [Jennifer Manuzak, Jennifer Manuel, Kathryn McCollister, Dustin Duncan] as well as NIH program staff: Gerald Sharp, Lori Zimand, Richard Jenkins, Michael Stirratt, & Sonia Lee.
FUNDING
Although NIH funded this research, they do not necessarily endorse these findings. AMETHST was supported by a grant from the National Institutes of Health (UG3 AI169652, Grov/Carrico MPI) as well as the CUNY-Einstein-Rockefeller Center for AIDS Research (P30 AI124414, Goldstein). Drew A. Westmoreland was supported in part by K01 AA029047
Footnotes
ETHICS APPROVAL
The study was approved by the Institutional Review Board (IRB) of CUNY and a waiver of parental consent was obtained for participants aged 16 and 17.
CONSENT TO PARTICIPATE
Informed consent was obtained from all individual participants included in the study.
COMPETING INTERESTS
None to report
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