A small number of studies have examined changes in substance use behavior following the onset of the pandemic. One study found substance use decreased but frequency of use increased among adolescents following the implementation of social distancing in Canada . Similarly, another study found decreases in the likelihood of using alcohol but increases in frequency among those who continued to use alcohol during the pandemic among US adults . However, the impact of COVID-19 may also vary across subpopulations. Studies have observed an increase in cannabis use among casino gamblers , no increase in cannabis use among a sample of people living with HIV , and decreases in both cannabis and other illegal drug use among sexual minority men . Given these findings, it is important to examine changes in substance use behaviors among groups at high risk for negative health outcomes. For example, young adults may be particularly vulnerable to the pandemic’s detrimental impact on mental health . Furthermore, sexual and gender minorities reporthigher rates of substance use and prevalence of substance use disorders than their peers. For example, two studies found lifetime marijuana use was 40.4 % among transgender youth and 65.0 % among young gay men , 1.5–1.9 times greater than peers. Accordingly, sexual and gender minority young adults are uniquely vulnerable to negative health outcomes during the pandemic given existing high rates of substance use . This study leverages a cohort with longitudinal observations of the same individuals before and after the pandemic onset to examine changes in both prevalence and frequency of drug use among young men who have sex with men and young transgender women.
All data for this study come from an ongoing longitudinal cohort study of YMSM-YTW . Data collection for this cohort began in February 2015 and remains ongoing. Participants included recruitment from two prior cohorts, Project Q2 and Crew 450 , as well as new enrollment with participants recruited via venue-based, online, and peer recruitment. All cohort members were required to meet the following criteria: 16–29 years old at enrollment, male assigned at birth , speak English, report a sexual encounter with a man in the previous year or identify as gay or bisexual, and willing to attend in-person research visits in Chicago. Comprehensive details regarding the cohort can be found elsewhere . Cohort participants were eligible for one study visit every six months. Participants were eligible for the current analysis if they completed a visit after the shelter in place order in Illinois took effect on March 21 st, 2020 by the date of analysis and also had at least one other visit within the last year and a half prior to the order. Data were included for up to the two most recent visits before the onset of the pandemic and one observation after the pandemic’s onset. Accordingly, cannabis grow tent the analysis included 458 participants of which 440 provided data on 3 visits and 18 provided data on 2 visits, for a total of and 1356 visits. We examined descriptive statistics regarding past 30-day drug use prevalence by drug category across visits. We also examined alluvial plots to examine transition between frequencies across visits. Subsequently, we modeled changes in past 30-day prevalence and changes in frequency of use. All models were Bayesian multilevel models and included a random intercept to account for multiple observations per participant, using the default improper flat priors for fixed effects . Change in prevalence was examined using a logistic model. Change in frequency was examined using a sequential ordinal model with a logistic distribution, commonly known as a continuation ratio model .
Participants were assigned their highest indicated frequency for non-marijuana drug use. The main exposure variable of interest was a dichotomous indicator designating observations following the onset of the pandemic . First, we examined a model with independent association of the pandemic. Second, we examined models with age, HIV status, and gender identity as covariates. Finally, we conducted a two-part sensitivity analysis for non-marijuana drug use frequency to ensure participants changing drug types did not bias results. First, we excluded participants that changed their most frequently used non-marijuana drug across visits. Second, we utilized a sum score of frequency across all non-marijuana drugs as the outcome by summing the midpoints number of occasions for each drugThis study found little evidence of changes in marijuana prevalence or frequency of use in a large cohort of YMSM-YTW. However, a decrease in non-marijuana drug use and a slight increase in the frequency of drug use was observed among individuals who continued to use these substances. These findings highlight the complexity of changes in drug use behaviors during the COVID-19 pandemic that may uniquely impact individuals with different levels of substance use. While the observed decrease in non-marijuana drug use could be driven by reduced social occasions to use drugs , studies observing related but distinct groups from the current sample have found inconsistent results. One study in an older sample of MSM observed declines in drug use and a different study of people living with HIV finding no significant differences in drug use . Yet, studies of general sample adolescents reported a decrease in prevalence of alcohol and marijuana use . Therefore, accumulating evidence suggests the pandemic may differentially impact drug use behaviors among certain subpopulations. Future studies should consider the potential for heterogeneity in response to the pandemic across age, sexual identity, and HIV status. In addition, two prior studies have observed decreases in prevalence but increases in frequency of use among alcohol and marijuana during the COVID-19 pandemic.
Although we observed no changes in marijuana use, these findings considered together may indicate the COVID-19 pandemic is particularly detrimental to habitual substance users but be less influential to casual users. Accordingly, there is an urgent need for further data on substance use disorders which may also be impacted by barriers to substance use treatment and harm reduction services during the pandemic . Indeed, the increased frequency of non-marijuana drug use may indicate an extended need for substance use treatment, even following the widespread adoption of COVID-19 vaccines and these services will be particularly important for subpopulations such as YMSM-YTW with higher prevalence of use. This study had a number of limitations. The impact of the pandemic cannot be disentangled from the recent legalization of recreationalmarijuana use in Illinois. Drug use frequency was measured with an ordinal scale that could not capture subtle changes in drug use. Drugs were categorized in broad groups that do not reflect risk differences across specific drugs. We could not provide separate estimates by gender identity due to small cell counts. Finally, these data come from a large and diverse sample important to drug use epidemiology but was not a probability sample. Despite these limitations, we believe this study provides important initial evidence documenting decreases in prevalence but potential increases in frequency of non-marijuana drug use among YMSM-YTW. Future studies should continue to explore the impact the pandemic may have on substance use behaviors and the potential for heterogeneity in the pandemic’s effects across important subpopulations.The United States’ 2019 outbreak of e-cigarette or vaping-associated lung injuries sickened over 2800 patients, causing 68 deaths . The geographic distribution of cases was consistent with a contaminant in locally-distributed products . CDC ultimately identified vitamin E acetate—an additive most commonly found in informally-sourced vaporizable marijuana concentrates—as the outbreak’s primary cause . Although CDC stopped collecting EVALI case data in February 2020, future outbreaks remain a threat as vitamin E acetate and other chemicals unsafe for inhalation still can be added to informally-sourced marijuana products. State marijuana laws may offer a means to reduce the scale of such outbreaks if they influence the market penetration of contaminated marijuana concentrates or the types of marijuana products consumers use. Prior work on the relationship between state marijuana policies and EVALI suggests that the case prevalence was lower in states that had legalized recreational marijuana but higher where only medical marijuana had been legalized . However, MM policies are not homogenous, and specific policy details are known to influence marijuana use and abuse . With vaping as the second most popular mode of marijuana use after smoking , policy attributes that might affect mode of use—e. g., restrictions on home cultivation, restrictions on combustible marijuana use, the presence of operational dispensaries—could be particularly consequential. Simply put, decreasing the number of people who vape marijuana concentrates should decrease a state’s EVALI incidence when contaminated marijuana concentrates enter its market.
Given the potential importance of marijuana policy details for consumer use and EVALI, this study’s objective was to estimate the relationship of states’ 2019 EVALI prevalence to their recreational and medical marijuana policies, accounting for medical marijuana policy attributes that might affect mode of use. Total EVALI cases were obtained for each US state via government websites and departments of health as of the second week of January 2020 to ensure inclusion of cases reported over the winter holidays. . These data were matched to the implementation dates of states’ RM and MM laws, as well as three specific MM policy attributes — allowing home cultivation, having operational dispensaries, and prohibiting combustible use, with indicator variables for each defined to capture whether the policy/policy attribute was in effect as of August 1, 2019. This cutoff ruled out reverse causality by ensuring that the grow lights for cannabis policies considered here were not implemented in response to the EVALI outbreak: CDC first issued its recommendation that all clinicians report cases of unexplained pulmonary disease among people with a history of vaping on August 2nd, 2019 . Population data from the US Census were used to account for differences in state population sizes . State-representative survey data from the 2016–2019 Behavioral Risk Factor Surveillance System marijuana modules —fielded in 21 states—were also matched to the aforementioned marijuana policies. These data were used to estimate associations between marijuana policy attributes and respondents’ reports of vaping as their primary mode of marijuana use. Neither the marijuana module data nor the EVALI case counts covered Washington, D.C. We used Stata for all analyses. First, we mapped EVALI case counts alongside state marijuana policies to clarify geographic variation. Multivariable negative binomial regression was then used to estimate the relationship between states’ total 2019 EVALI cases and two mutually exclusive marijuana policy indicators: RM+MM legalization and MM-only legalization. The count data exposure variable was set to the number of state residents ages 13–64 years, covering the vast majority of EVALI case ages . To clarify the potential implications of policy attributes, a second specification added three binary covariates, indicating MM-only states that allowed home cultivation, had an open dispensary, and prohibited combustible marijuana use as of August 1, 2019. Four sensitivity checks were considered. First, we added a covariate for the percent of state residents under age-35, the age-group responsible for 76% of EVALI cases . This addresses the possibility that larger youth/young adult populations might impact the informal market for cannabis, allowing for greater market penetration of contaminated vaping products. Second, to increase confidence that findings were not driven by state differences in EVALI case detection or reporting practices, regressions were repeated with case counts limited to hospitalized EVALI cases, as states were asked to report hospitalized EVALI case numbers to CDC regularly in December 2019 and January 2020 . Finally, to ensure that findings were not driven by key outliers, sensitivity checks repeated the full sample regression for both all EVALI cases and hospitalized cases only, first without Ohio and Pennsylvania, whose dispensaries sold flower despite prohibiting combustible use, and then without Utah and West Virginia, whose MM laws went into effect before residents could legally obtain MM in-state. Robustness checks repeated all analyses as linear regressions, specifying the outcome as EVALI cases per 100,000 residents aged 13–64. Finally, BRFSS analyses assessed whether policies associated with more EVALI cases were also associated with a higher likelihood of people who use marijuana choosing vaping as their primary mode of use.