Faculty Bibliography

Alcohol use disorder is a major contributor to the morbidity and mortality burden worldwide. It often coexists with other psychiatric disorders; however, the nature of this comorbidity is still a matter of debate. In this Series paper, we examine the main psychiatric disorders associated with alcohol use disorder, including the prevalence of co-occurring disorders, the temporal nature of the relationship, and mechanisms that might explain comorbidity across the lifespan. Overall, this disorder co-occurs with a wide range of other psychiatric disorders, especially those disorders involving substance use and violent or aggressive behaviour. The causal pathways between alcohol use disorder and other psychiatric disorders are heterogeneous. Hypotheses explaining these relationships include reciprocal direct causal associations, shared genetic and environmental causes, and shared psychopathological characteristics of broader diagnostic entities (eg, externalising disorders). Efforts to untangle the associations between alcohol use disorder and other disorders across the lifespan remain a crucial avenue of research.

BACKGROUND:Prescription drug monitoring programs (PDMP), by reducing access to prescribed opioids (POs), may contribute to a policy environment in which some people with opioid dependence are at increased risk for transitioning from POs to heroin/other illegal opioids. This study examines how PDMP adoption and changes in the characteristics of PDMPs over time contribute to changes in fatal heroin poisoning in counties within states from 2002 to 2016. METHODS:Latent transition analysis to classify PDMPs into latent classes (Cooperative, Proactive, and Weak) for each state and year, across three intervals (1999-2004, 2005-2009, 2010-2016). We examined the association between probability of PDMP latent class membership and the rate of county-level heroin poisoning death. RESULTS:After adjustment for potential county-level confounders and co-occurring policy changes, adoption of a PDMP was significantly associated with increased heroin poisoning rates (22% increase by third year post-adoption). Findings varied by PDMP type. From 2010-2016, states with Cooperative PDMPs (those more likely to share data with other states, to require more frequent reporting, and include more drug schedules) had 19% higher heroin poisoning rates than states with Weak PDMPs (adjusted rate ratio [ARR] = 1.19; 95% CI = 1.14, 1.25). States with Proactive PDMPs (those more likely to report outlying prescribing and dispensing and provide broader access to law enforcement) had 6% lower heroin poisoning rates than states with No/Weak PDMPs (ARR = 0.94; 95% CI = 0.90, 0.98). CONCLUSION/CONCLUSIONS:There is a consistent, positive association between state PDMP adoption and heroin poisoning mortality. However, this varies by PDMP type, with Proactive PDMPs associated with a small reduction in heroin poisoning deaths. This raises questions about the potential for PDMPs to support efforts to decrease heroin overdose risk, particularly by using proactive alerts to identify patients in need of treatment for opioid use disorder. Future research on mechanisms explaining the reduction in heroin poisonings after enactment of Proactive PDMPs is merited.

BACKGROUND:Little is known about recent nonmedical prescription tranquilizer and stimulant use trends in Latin America. We tested whether recent trends among students in three South American countries differed by sex over time. METHODS:Three countries independently collected National School Students Survey on Drugs. Students in 8th, 10th, and 12th grades were sampled in Argentina (2007-2014, N = 328,202), Chile (2007-2015, N = 136,379), and Uruguay (2007-2016, N = 32,371). Weighted linear regression models predicted the prevalences and trends over time of past-year nonmedical tranquilizer and stimulant use by country, and tested whether trends differed by sex, adjusting for school type and grade. RESULTS:In Argentina from 2007 to 2014, past-year nonmedical prescription tranquilizer (girls: 2.8 to 2.6%, boys: 2.5 to 2.3%) and stimulant (girls: 1.7 to 1.3%, boys: 1.9 to 1.5%) use trends did not differ by sex. In Chile from 2007 to 2015, nonmedical prescription tranquilizer use trends significantly differed comparing girls (3.9 to 10%) with boys (3.2 to 6.9%); stimulant use trends did not differ comparing girls (1.6 to 2.0%) with boys (2.0 to 1.3%). In Uruguay from 2007 to 2014 and 2014-2016, past-year nonmedical prescription tranquilizer (girls: 5.1 to 6.6%; boys: 2.8 to 4.2%) and stimulant (girls: 1.8 to 0.7%; boys: 1.8 to 0.7%) use trends did not differ by sex. CONCLUSIONS:Trends of nonmedical prescription tranquilizer use recently increased in Chile and Uruguay, widening by sex over time in Chile only. The drivers of increasing tranquilizer use among girls in Chile and Uruguay merit further investigation.

Introduction/UNASSIGNED:Viral load is one of the most important determinants for HIV transmission. Identification of people with high viral load (PHVL) can be effective in limiting onward HIV transmission. In order to improve the identification of these individuals within risk networks, we determined a) the number of PHVL recruited through risk networks b) their socio-demographic, behavioural and clinical characteristics and c) the characteristics of individuals who referred these PHVL to the study. Methodology/UNASSIGNED:From November 2013 to March 2016, in Odessa, Ukraine, Transmission Reduction Intervention Project (TRIP) was implemented to identify people recently infected with HIV within the risk networks of "seeds" and "venues" where they engaged in risk behaviour. Results/UNASSIGNED:TRIP identified 53 PHVL, of whom 32 (60%) injected drugs; 42 (79%) were unaware of their HIV status; 25 (47%) had more than one sex partner, and only 14 (26%) were using condoms. There were 164 people who referred individuals into the study; 33 of them (20%) referred PHVL. In terms of referrers, those with lower than secondary level of education, not living with a sex partner, and reporting regular condom use were significantly more likely (p < 0.05) to refer PHVL. Most PHVL (38, 72%) and their referrers (27, 82%) were found through venues. Conclusions/UNASSIGNED:In Odessa city, PHVL are at high risk of transmitting HIV as the majority inject drugs, do not know their HIV status, and have unprotected sex and/or multiple partners. Targeting these individuals for HIV prevention, harm reduction and initiation of antiretroviral treatment (ART) is urgent.

OBJECTIVE:This qualitative study identifies and describes experiences and challenges to retention of individuals with opioid use disorder (OUD) who participated in a low-threshold combined buprenorphine-peer support treatment program in Baltimore. METHODS:In-depth semi-structured interviews with staff and former clients of the Project Connections Buprenorphine Program (PCBP) (9 people) and focus group discussions with current and previous clients of PCBP (7 people) were conducted. Content analysis was used to extract themes regarding barriers to enrolling and remaining in, and transitioning from the program. RESULTS:Primary challenges identified by the participants included struggles with cravings and symptoms of withdrawal, comorbid mental health issues, criminal justice system involvement, medication stigma, and conflicts over level of flexibility regarding program requirements and the role of employment. CONCLUSIONS:This study identified several obstacles clients face when seeking care through a combined buprenorphine-peer support model. Findings highlight potential programmatic factors that can be improved and additional resources that may support treatment retention rates and better outcomes. Despite challenges, low-threshold and community-based programs can increase access to effective maintenance treatment for OUD, especially among vulnerable populations who may not have access to formal health services.

Prescription and illicit opioids were involved in over 42,000 deaths in the USA in 2016. Rural counties experience higher rates of opioid prescribing and, although opioid prescribing rates have fallen in recent years, the rate of decline is less in rural areas. The sociocultural context of rural life may impact opioid misuse in important ways; however, little research directly explores this possibility. We performed a systematic review of English-language manuscripts in U.S. context to determine what is known about social networks, norms, and stigma in relation to rural opioid misuse. Of nine articles identified and reviewed, two had only primary findings associated with social networks, norms, or stigma, five had only secondary findings, and two had both primary and secondary findings. The normalization of prescription opioid use along with environmental factors likely impacts the prevalence of opioid misuse in rural communities. Discordant findings exist regarding the extent to which social networks facilitate or protect against nonmedical opioid use. Lastly, isolation, lack of treatment options, social norms, and stigma create barriers to substance use treatment for rural residents. Although we were able to identify important themes across multiple studies, discordant findings exist and, in some cases, findings rely on single studies. The paucity of research examining the role of social networks, norms, and stigma in relation to nonmedical opioid use in rural communities is evident in this review. Scholarship aimed at exploring the relationship and impact of rurality on nonmedical opioid use is warranted.

Objectives. To estimate the number of lives saved from firearms suicide with expansions of gun restrictions based on mental health compared with the number who would be unnecessarily restricted. Methods. Agent-based models simulated effects on suicide mortality resulting from 5-year ownership disqualifications in New York City for individuals with any psychiatric hospitalization and, more broadly, anyone receiving psychiatric treatment. Results. Restrictions based on New York State Office of Mental Health-identified psychiatric hospitalizations reduced suicide among those hospitalized by 85.1% (95% credible interval = 36.5%, 100.0%). Disqualifications for anyone receiving psychiatric treatment reduced firearm suicide rates among those affected and in the population; however, 244 820 people were prohibited from firearm ownership who would not have died from firearm suicide even without the policy. Conclusions. In this simulation, denying firearm access to individuals in psychiatric treatment reduces firearm suicide among those groups but largely will not affect population rates. Broad and unfeasible disqualification criteria would needlessly restrict millions at low risk, with potential consequences for civil rights, increased stigma, and discouraged help seeking.

Prior studies on substance use in Brazil have not focused on opioid misuse, previously thought to be nearly non-existent. This paper presents new findings on heroin and non-medical use of opioid analgesics. Data come from the 2015 Brazilian Household Survey on Substance Use (BHSU-3), a nationally representative survey estimating epidemiological parameters related to substance use by residents across Brazil. BHSU-3 used stratified multi-stage probability sampling across multiple geographic domains of interest, resulting in 16,273 interviews with household residents. Lifetime heroin use among Brazilians was 0.3 (95% C.I:0.2-0.4). Lifetime, past-year, and past-month non-medical use of opioid analgesics were respectively 2.9 (95%C.I.:2.3-3.4), 1.4 (95%C.I.:1.1-1.7) and 0.6 (95%C.I.:0.4-0.8). Past-year prevalence of non-medical opioid analgesics use was lower among males [Prevalence Ratio (PR): 0.54 (95% C.I.:0.36-0.78)], those aged 12-24 [0.56 (95% C.I.:0.34-0.92)], persons with monthly family incomes between R$1,501-3,000 [0.59 (95% C.I.:0.38-0.92)] or greater than R$3,000 [0.64 (95% C.I.:0.42-0.98)], and persons who were unemployed [0.65 (95% C.I.:0.46-0.92)]. Non-medical use of opioids in Brazil may be more prevalent than previously recognised. Proper measurement and evaluation of opioid misuse across Brazil and other Latin American countries is critical to understand and prevent opioid-related harms.

OBJECTIVE:Understand how insurance impacts access to services among people who have injected drugs. METHODS:1748 adults who have injected drugs were assessed at twice-annual study visits between 2006 and 2017 (18,869 visits). Use of specialty substance use treatment, receipt of buprenorphine, and having a regular source of medical care were assessed for association with concurrent insurance coverage. Random intercept logistic regression was used to adjust for potential confounders. RESULTS:When participants acquired insurance, they were more likely to report specialty substance use treatment (aOR 2.0, 95% CI 1.6 to 2.5), a buprenorphine prescription (aOR 3.3, 95% CI 2.0 to 5.5), and a regular source of medical care (aOR 6.3, 95% CI 5.1 to 7.8). CONCLUSION/CONCLUSIONS:Insurance is associated with increased use of three important services for individuals who inject drugs. IMPLICATIONS/CONCLUSIONS:Expanding insurance may facilitate access to substance use treatment and other needed health services.

BACKGROUND:Predicting which individuals who are prescribed buprenorphine for opioid use disorder are most likely to experience an overdose can help target interventions to prevent relapse and subsequent consequences. METHODS:We used Maryland prescription drug monitoring data from 2015 to identify risk factors for nonfatal opioid overdoses that were identified in hospital discharge records in 2016. We developed a predictive risk model for prospective nonfatal opioid overdoses among buprenorphine patients (N = 25,487). We estimated a series of models that included demographics plus opioid, buprenorphine and benzodiazepine prescription variables. We applied logistic regression to generate performance measures. RESULTS:About 3.24% of the study cohort had ≥1 nonfatal opioid overdoses. In the model with all predictors, odds of nonfatal overdoses among buprenorphine patients were higher among males (OR = 1.39, 95% CI:1.21-1.62) and those with more buprenorphine pharmacies (OR = 1.19, 95% CI:1.11-1.28), 1+ buprenorphine prescription paid by Medicaid (OR = 1.21, 95% CI:1.02-1.48), Medicare (OR = 1.93, 95% CI:1.63-2.43), or a commercial plan (OR = 1.98, 95% CI:1.30-2.89), 1+ opioid prescription paid by Medicare (OR = 1.30, 95% CI:1.03-1.68), and more benzodiazepine prescriptions (OR = 1.04, 95% CI:1.02-1.05). The odds were lower among those with longer days of buprenorphine (OR = 0.64, 95% CI:0.60-0.69) or opioid (OR = 0.79, 95% CI:0.65-0.95) supply. The model had moderate predictive ability (c-statistic = 0.69). CONCLUSIONS:Several modifiable risk factors, such as length of buprenorphine treatment, may be targets for interventions to improve clinical care and reduce harms. This model could be practically implemented with common prescription-related information and allow payers and clinical systems to better target overdose risk reduction interventions, such as naloxone distribution.