Faculty Bibliography

AIM/OBJECTIVE:To quantify the trends in frequent and occasional cannabis vaping, demographic differences and concurrent nicotine and alcohol use. DESIGN/METHODS:Observational study. Survey-weighted multinomial logistic regression models assessed trends and disparities in past 30-day cannabis use. Trends were assessed overall and by sex, race/ethnicity, parental education and urbanicity. Multinomial logistic regression models also estimated associations of cannabis use (none, use without vaping, use with vaping) with past 2-week binge drinking and past 30-day nicotine/tobacco use. SETTING/METHODS:United States, 2017-19. PARTICIPANTS/METHODS:Participants in the national Monitoring the Future (n = 51 052) survey. MEASUREMENTS/METHODS:Past 30-day frequent cannabis use (six or more times/30 days) and past 30-day occasional use (one to five times/30 days), with and without vaping. FINDINGS/RESULTS:Past 30-day frequent cannabis use with vaping and occasional use with vaping rose from 2017 to 2019. Past 30-day frequent and occasional cannabis use without vaping declined. Certain groups, such as Hispanic/Latino or lower socio-economic status adolescents, experienced particularly notable increases in frequent cannabis use with vaping (e.g. prevalence among Hispanic/Latino adolescents). Adolescents who reported smoking and vaping nicotine, and 10+ occasions of binge drinking, were 42.28 [95% confidence interval (CI) = 33.14-53.93] and 10.09 (95% CI = 4.51-22.53) times more likely to report past 30-day cannabis use with vaping, respectively, compared with no use. DISCUSSION/CONCLUSIONS:Cannabis use without vaping appears to be declining among adolescents in the United States, while cannabis use with vaping is accelerating; frequent cannabis vaping is especially increasing, with consistent increases across almost all adolescent demographic groups. Cannabis use among US adolescents remains highly associated with other substance use.

BACKGROUND AND AIM/OBJECTIVE:In Uruguay, residents age 18 and older seeking legal cannabis must register with the government and choose one of three supply mechanisms: self-cultivation, non-profit cannabis clubs or pharmacies. This is the first paper to measure the association between type of legal cannabis supply mechanism and traffic crashes involving injuries. DESIGN/METHODS:Ecological study using ordinary least squares regression to examine how department-level variation in registrations (overall and by type) is associated with traffic crashes involving injuries. SETTING/METHODS:Uruguay. CASES/METHODS:532 department-quarters. MEASUREMENTS/METHODS:Quarterly cannabis registration counts at the department level and incident-level traffic crash data were obtained from government agencies. The analyses controlled for department-level economic and demographic characteristics and, as a robustness check, we included traffic violations involving alcohol for departments reporting this information. Department-level data on crashes, registrations and alcohol violations were denominated by the number of residents ages 18 and older. FINDINGS/RESULTS:From 2013 to 2019, the average number of registrations at the department-quarter level per 10 000 residents age 18 and older for self-cultivation, club membership and pharmacy purchasing were 17.7 (SD = 16.8), 3.6 (SD = 8.6), and 25.1 (SD = 50.4), respectively. In our multivariate regression analyses, we did not find a statistically significant association between the total number of registrations and traffic crashes with injuries (β = -0.007; P = 0.398; 95% CI = -0.023, 0.01). Analyses focused on the specific supply mechanisms found a consistent, positive and statistically significant association between the number of individuals registered as self-cultivators and the number of traffic crashes with injuries (β = 0.194; P = 0.008; 95% CI = 0.058, 0.329). Associations for other supply mechanisms were inconsistent across the various model specifications. CONCLUSIONS:In Uruguay, the number of people allowed to self-cultivate cannabis is positively associated with traffic crashes involving injuries. Individual-level analyses are needed to assess better the factors underlying this association.

BACKGROUND:States have enacted multiple types of laws, with a variety of constituent provisions, in response to the opioid epidemic, often simultaneously. This temporal proximity and variation in state-to-state operationalization has resulted in significant challenges for empirical research on their effects. Thus, expert consensus can be helpful to classify laws and their provisions by their degree of helpfulness and impact. METHODS:We conducted a four-stage modified policy Delphi process to identify the top 10 most helpful and 5 most harmful provisions from eight opioid-related laws. This iterative consultation with six types of opioid experts included a preliminary focus group (n=12), two consecutive surveys (n=56 and n=40, respectively), and a final focus group feedback session (n=5). RESULTS:On a scale of very harmful (0) to very helpful (4), overdose Good Samaritan laws received the highest average helpfulness rating (3.62, 95% CI: 3.48-3.75), followed by naloxone access laws (3.37, 95% CI: 3.22-3.51), and pain management clinic laws (3.08, 95% CI: 2.89-3.26). Drug-induced homicide (DIH) laws were rated the most harmful (0.88, 95% CI: 0.66-1.11). Impact ratings aligned similarly, although Medicaid laws received the second highest overall impact rating (3.71, 95% CI: 3.45, 3.97). The two most helpful provisions were naloxone standing orders (3.94, 95% CI: 3.86-4.02) and Medicaid coverage of medications for opioid use disorder (MOUD) (3.89, 95% CI: 3.82). Mandatory minimum DIH laws were the most harmful provision (0.73, 95% CI 0.53-0.93); followed by requiring prior authorization for Medicaid coverage of MOUD (1.00 95% CI: 0.72-1.27). CONCLUSION/CONCLUSIONS:Overall, experts rated laws and provisions that facilitated harm reduction efforts and access to MOUD as most helpful. Laws and provisions rated as most harmful criminalized substance use and placed restrictions on access to MOUD. These ratings provide a foundation for evaluating the overall overdose policy environment for each state.

OBJECTIVE/UNASSIGNED:In the United States, adult cannabis use has increased over time, but less information is available on time trends in cannabis use disorder. The authors used Veterans Health Administration (VHA) data to examine change over time in cannabis use disorder diagnoses among veterans, an important population subgroup, and whether such trends differ by age group (<35 years, 35-64 years, ≥65 years), sex, or race/ethnicity. METHODS/UNASSIGNED:VHA electronic health records from 2005 to 2019 (range of Ns per year, 4,403,027-5,797,240) were used to identify the percentage of VHA patients seen each year with a cannabis use disorder diagnosis (ICD-9-CM, January 1, 2005-September 30, 2015; ICD-10-CM, October 1, 2015-December 31, 2019). Trends in cannabis use disorder diagnoses were examined by age and by race/ethnicity and sex within age groups. Given the transition in ICD coding, differences in trends were tested within two periods: 2005-2014 (ICD-9-CM) and 2016-2019 (ICD-10-CM). RESULTS/UNASSIGNED:In 2005, the percentages of VHA patients diagnosed with cannabis use disorder in the <35, 35-64, and ≥65 year age groups were 1.70%, 1.59%, and 0.03%, respectively; by 2019, the percentages had increased to 4.84%, 2.86%, and 0.74%, respectively. Although the prevalence of cannabis use disorder was consistently higher among males than females, between 2016 and 2019, the prevalence increased more among females than males in the <35 year group. Black patients had a consistently higher prevalence of cannabis use disorder than other racial/ethnic groups, and increases were greater among Black than White patients in the <35 year group in both periods. CONCLUSIONS/UNASSIGNED:Since 2005, diagnoses of cannabis use disorder have increased substantially among VHA patients, as they have in the general population and other patient populations. Possible explanations warranting investigation include decreasing perception of risk, changing laws, increasing cannabis potency, stressors related to growing socioeconomic inequality, and use of cannabis to self-treat pain. Clinicians and the public should be educated about the increases in cannabis use disorder in general in the United States, including among patients treated at the VHA.

BACKGROUND:The United States overdose crisis continues unabated. Despite efforts to increase capacity for treating opioid use disorder (OUD) in the U.S., how actual treatment receipt compares to need remains unclear. In this cross-sectional study, we estimate progress in addressing the gap between OUD prevalence and OUD treatment receipt at the national and state levels from 2010 to 2019. METHODS:We estimated past-year OUD prevalence rates based on the U.S. National Survey on Drug Use and Health (NSDUH), using adjustment methods that attempt to account for OUD underestimation in national household surveys. We used data from specialty substance use treatment records and outpatient pharmacy claims to estimate the gap between OUD prevalence and number of persons receiving medications for opioid use disorder (MOUD) during the past decade. RESULTS:Adjusted estimates suggest past-year OUD affected 7,631,804 individuals in the U.S. in (2,773 per 100,000 adults 12+), relative to only 1,023,959 individuals who received MOUD (365 per 100,000 adults 12+). This implies approximately 86.6% of individuals with OUD nationwide who may benefit from MOUD treatment do not receive it. MOUD receipt increased across states over the past decade, but most regions still experience wide gaps between OUD prevalence and MOUD receipt. CONCLUSIONS:Despite some progress in expanding access to MOUD, a substantial gap between OUD prevalence and treatment receipt highlights the critical need to increase access to evidence-based services.

As opioid prescribing has declined, it is unclear how the landscape of prescription pain treatment across the US has changed. We used nationally-representative data from the Medical Expenditure Health Survey, 2014-2018 to examine trends in prescriptions for opioid and non-opioid pain medications, including acetaminophen, non-steroidal anti-inflammatory drugs (NSAIDs), gabapentinoids, and antidepressants among US adults with self-reported pain. Overall, from 2014-2018, the percentage of participants receiving a prescription for opioids declined, (38.8% vs. 32.8%), remained stable for NSAIDs (26.8% vs. 27.7%), and increased for acetaminophen (1.6% vs. 2.3%), antidepressants (9.6% vs. 12.0%) and gabapentinoids (13.2% vs. 19.0%). In this period, the adjusted odds of receiving an opioid prescription decreased (aOR=0.93, 95% CI=0.90-0.96), while the adjusted odds of receiving antidepressant, gabapentinoid and acetaminophen prescriptions increased (antidepressants: aOR=1.08, 95% CI=1.03-1.13 gabapentinoids: aOR=1.11, 95% CI=1.06-1.17; acetaminophen: aOR=1.10, 95% CI: 1.02-1.20). Secondary analyses stratifiying within the 2014-2016 and 2016-2018 periods revealed particular increases in prescriptions for gabapentinoids (aOR=1.13, 95% CI=1.05-1.21) and antidepressants (aOR=1.23, 95% CI=1.12-1.35) since 2016.

OBJECTIVE:Polysubstance use may complicate treatment outcomes for individuals who use opioids. This research aimed to examine the prevalence of polysubstance use in an opioid use disorder treatment trial population and polysubstance use's association with opioid relapse and craving. METHODS:This study is a secondary data analysis of individuals with opioid use disorder who received at least one dose of medication (n = 474) as part of a 24-week, multi-site, open label, randomized Clinical Trials Network study (CTN0051, X:BOT) comparing the effectiveness of extended-release naltrexone versus buprenorphine. Models examined pretreatment polysubstance use and polysubstance use during the initial 4 weeks of treatment on outcomes of relapse by week 24 of the treatment trial and opioid craving. RESULTS:Polysubstance use was generally not associated with treatment outcomes of opioid relapse and craving. Proportion of days of pretreatment sedative use was associated with increased likelihood of opioid relapse (OR: 1.01, 95 % CI: 1.00-1.02). Proportion of days of cocaine use during the initial 4 weeks of treatment was associated with increased likelihood of opioid relapse (OR: 1.05, 95 % CI: 1.01-1.09) but this effect was no longer significant once the potential of confounding by opioid use was considered. Sedative use during initial 4 weeks of treatment was associated with increased opioid craving (b: 0.77, 95 % CI: 0.01-1.52). The study found no other significant relationships. CONCLUSIONS:In the current study population, polysubstance use was only marginally associated with 24-week treatment outcomes.

Structural racism is increasingly recognized as a key driver of health inequities and other adverse outcomes. This paper focuses on structural racism as an "upstream" institutionalized process, how it creates health inequities and how structural racism persists in spite of generations of efforts to end it. So far, "downstream" efforts to reduce these health inequities have had little success in eliminating them. Here, we attempt to increase public health awareness of structural racism and its institutionalization and sociopolitical supports so that research and action can address them. This paper presents both a theoretic and an analytic approach to how structural racism contributes to disproportionate rates of HIV/AIDS and related diseases among oppressed populations. We first discuss differences in disease and health outcomes among people who use drugs (PWUD) and other groups at risk for HIV from different racial and ethnic populations. The paper then briefly analyzes the history of racism; how racial oppression, class, gender and other intersectional divisions interact to create health inequities; and how structural racism is institutionalized in ways that contribute to disease disparities among people who use drugs and other people. It examines the processes, institutions and other structures that reinforce structural racism, and how these, combined with processes that normalize racism, serve as barriers to efforts to counter and dismantle the structural racism that Black, indigenous and Latinx people have confronted for centuries. Finally, we discuss the implications of this analysis for public health research and action to undo racism and to enhance the health of populations who have suffered lifetimes of racial/ethnic oppression, with a focus on HIV/AIDS outcomes.

BACKGROUND:Substance-related interactions with the criminal justice system are a potential touchpoint to identify people at risk for firearm violence. We used an agent-based model to simulate the change in firearm violence after disqualifying people from owning a firearm given prior alcohol- and drug-related misdemeanors. METHODS:We created a population of 800,000 agents reflecting a 15% sample of the adult New York City population. RESULTS:Disqualification from purchasing firearms for 5 years after an alcohol-related misdemeanor conviction reduced population-level rates of firearm homicide by 1.0% [95% CI 0.4-1.6%] and suicide by 3.0% [95% CI 1.9-4.0%]. Disqualification based on a drug-related misdemeanor conviction reduced homicide by 1.6% [95% CI 1.1-2.2%] and suicide by 4.6% [95% CI 3.4-5.8%]. Reductions were generally 2 to 8 times larger for agents meeting the disqualification criteria. CONCLUSIONS:Denying firearm access based on a history of drug and alcohol misdemeanors may reduce firearm violence among the high-risk group. Enactment of substance use-related firearms denial criteria needs to be balanced against concerns about introducing new sources of disenfranchisement among already vulnerable populations.