Faculty Bibliography

BACKGROUND:Most hookah use studies have not included racial and ethnic minorities which limits our understanding of its use among these growing populations. This study aimed to investigate the individual characteristics of hookah use patterns and associated risk behaviors among an ethnically diverse sample of college students. METHODS:A cross-sectional survey of 2460 students (aged 18-25) was conducted in 2015, and data was analyzed in 2017. Descriptive statistics were used to present the sociodemographic characteristics, hookah use-related behavior, and binge drinking and marijuana use according to the current hookah use group, including never, exclusive, dual/poly hookah use. Multivariate logistic regression was conducted to examine how hookah related behavior and other risk behaviors varied by sociodemographics and hookah use patterns. RESULTS:Among current hookah users (n = 312), 70% were exclusive hookah users and 30% were dual/poly hookah users. There were no statistically significant differences in sociodemographic characteristics except for race/ethnicity (p < 0.05). Almost half (44%) of the exclusive hookah users reported having at least five friends who also used hookah, compared to 30% in the dual/poly use group. Exclusive users were less likely to report past year binge drinking (17%) and past year marijuana use (25%) compared to those in the dual/poly use group (44 and 48% respectively); p < 0.001. CONCLUSIONS:The socialization aspects of hookah smoking seem to be associated with its use patterns. Our study calls for multicomponent interventions designed to target poly tobacco use as well as other substance use that appears to be relatively common among hookah users.

INTRODUCTION/BACKGROUND:Qualitative analysis of Twitter posts reveals key insights about user norms, informedness, perceptions, and experiences related to opioid use disorder (OUD). This paper characterizes Twitter message content pertaining to medications for opioid use disorder (MOUD) and Naloxone. METHODS:In-depth thematic analysis was conducted of 1,010 Twitter messages collected in June 2019. Our primary aim was to identify user perceptions and experiences related to harm reduction (e.g., Naloxone) and MOUD (e.g., sublingual and Extended-release buprenorphine, Extended-release naltrexone, Methadone). RESULTS:Tweets relating to OUD were most commonly authored by general Twitter users (43.8%), private residential or detoxification programs (24.6%), healthcare providers (e.g., physicians, first responders; 4.3%), PWUOs (4.7%) and their caregivers (2.9%). Naloxone was mentioned in 23.8% of posts and authored most commonly by general users (52.9%), public health experts (7.4%), and nonprofit/advocacy organizations (6.6%). Sentiment was mostly positive about Naloxone (73.6%). Commonly mentioned MOUDs in our search consisted of Buprenorphine-naloxone (13.8%), Methadone (5.7%), Extended-release naltrexone (4.1%), and Extended-release buprenorphine (0.01%). Tweets authored by PWUOs (4.7%) most commonly related to factors influencing access to MOUD or adverse events related to MOUD (70.8%), negative or positive experiences with illicit substance use (25%), policies related to expanding access to treatments for OUD (8.3%), and stigma experienced by healthcare providers (8.3%). CONCLUSION/CONCLUSIONS:Twitter is utilized by a diverse array of individuals, including PWUOs, and offers an innovative approach to evaluate experiences and themes related to illicit opioid use, MOUD, and harm reduction.

Use of substances other than nicotine in e-cigarettes, especially marijuana, is becoming increasingly popular in the US. However, population-representative data on such poly-use (nicotine and marijuana) remains limited. We therefore conducted a cross-sectional logistic regression analysis of the 2018 Behavioral Risk Factor Surveillance System among 16 US states/territories with data on past 30-day marijuana use to describe the emerging dual nicotine and marijuana vaping population. We additionally examined trends in marijuana use, including marijuana vaping, from 2016 to 2018. Of the 131,807 participants studied, 3068 were current e-cigarette users, among whom 7.1% also vaped marijuana. Prevalence of nicotine-predominant, dual nicotine marijuana, and marijuana-predominant vaping was 3.36%, 0.38% and 1.09%, respectively. Compared to nicotine-predominant vapers, dual and marijuana-predominant vapers were older, had greater proportions of non-Whites, particularly Hispanics, and less likely to be current smokers (nicotine-predominant vs dual vs marijuana-predominant vaping: current tobacco use 44.7 vs 23.7 vs 11.1%). Proportion of dual vapers among current e-cigarette users was 8.6%, 2.6% and 7.1% for 2016, 2017 and 2018, respectively. Prevalence of marijuana use increased from 8.97% (2016) to 13.1% (2018) while no clear trend was observed for marijuana vaping. Dual nicotine and marijuana vaping is prevalent in the US, and compared to predominantly nicotine vapers such users have higher mean ages, and are more likely to be Blacks, Hispanics, and never cigarette smokers. Marijuana use overall increased from 2016 to 2018. Dual vapers represent a large and important emerging population that will require dedicated study of health effects and tailored regulatory strategies.

Background: Electronic dance music (EDM) party attendees are at high risk for use of various illegal drugs; however, little is known about their tobacco use. Understanding tobacco use patterns in this population at high risk for illegal drug use can inform multi-product interventions. Objectives: 954 EDM party attendees (ages 18-40) were surveyed in New York City in 2017. We estimated prevalence of use of cigarettes, hookah, cigars, other tobacco, and e-cigarettes and delineated correlates of current (past-month) use using bivariable and multivariable models. Results: Past-month use of cigarettes (36.2%), e-cigarettes (15.6%), cigars (12.5%), and hookah (11.7%) in particular was prevalent. In multivariable models, females were less likely to use e-cigarettes than males (adjusted prevalence ratio [aPR] = 0.63, p = .030), and those who attended graduate school were less likely to use cigarettes (aPR = 0.55, p = .003) and/or e-cigarettes (aPR = 0.33, p = .026). Past-year ecstasy/MDMA/Molly use was a risk factor for past-month use of cigarettes (aPR = 1.38, p = .013) and/or cigars (aPR = 1.61, p = .032), and past-year cocaine use was a risk factor for past-month use of cigarettes (aPR = 1.80, p < .001), cigars (aPR = 1.80, p = .013), other tobacco products (aPR = 3.05, p = .003), and/or e-cigarettes (aPR = 2.39, p = .003). 55.4% of ecstasy users and 60.3% of cocaine users were current cigarette smokers, but use of other products among users of these drugs was less prevalent (9.8-27.9%). Conclusions: Results suggest that current tobacco use is prevalent in this population who is also at high risk for use of drugs such as ecstasy and cocaine. Prevention and cessation efforts need to target tobacco users in this scene while incorporating components addressing illegal drug use.

INTRODUCTION/BACKGROUND:The prevalence of e-cigarette use has increased dramatically in the last decade in the U.S. Understanding the prevalence, patterns of use, and risk factor associations of e-cigarette use in pregnant women is particularly important, as this could have potential health implications for the mother and the developing child. METHODS:Using Behavioral Risk Factor Surveillance System Survey data from 2016 to 2018, adult women of reproductive age (18-49 years) who reported being pregnant (n=7,434) were studied. Self-reported current e-cigarette use was the main exposure. Other measures included combustible cigarette smoking status and high-risk behaviors (including other tobacco, marijuana, or heavy alcohol use; binge drinking; and others). All analyses were done in 2019. RESULTS:Approximately 2.2% of pregnant women reported current e-cigarette use, of whom 0.6% reported daily use. The highest prevalence of e-cigarette use was observed in the youngest age group of pregnant women (3.2%), with 41.7% of all pregnant current e-cigarette users being aged 18-24 years. There was a marked increase in the prevalence of current use of e-cigarettes among pregnant women from 1.9% in 2016 to 3.8% in 2018. Approximately 46% of pregnant current e-cigarette users reported concomitant cigarette smoking. Compared with pregnant never e-cigarette users, pregnant current e-cigarette users had a higher prevalence of other tobacco product use, marijuana use, heavy alcohol intake, binge drinking, and other high-risk behaviors. CONCLUSIONS:These findings underscore the need to strengthen prevention and policy efforts, specifically in the vulnerable subgroup of pregnant women.

Mobile technology has created the opportunity for health systems to provide low cost tobacco cessation assistance to patients. The goal of the present study was to examine the feasibility and effectiveness of an intervention (Text2Connect) that uses text messages to offer proactive connection to the New York State Smokers' Quitline. The electronic health record at two urban health systems was queried for patients who were current smokers and who had an outpatient visit between March 2015 and February 2016. Smokers (N = 4000) were sent an informational letter. Those who did not opt out (N = 3719) were randomized to one of 6 message sequences in order to examine the effect of theoretically informed message frames on response rates. Participants were sent a series of text messages at baseline and at 1 month and were asked to reply in order to be contacted by the state quitline (QL). After removing 1403 nonworking numbers, texts were sent to 2316 patients, and 10.0% (205/2060) responded with a QL request. Almost one quarter (23.6%, 486/2060) replied STOP and 66.4% (1369/2060) never responded. QL request rates were significantly higher when response efficacy messages were not used (p < .001). There were no differences by message framing on STOP requests (p > .05). The Text2Connect intervention was well accepted with a minority opting out. A 10% QL response rate is noteworthy given that only 5-7 brief outreach text messages were used. Results indicate that simple self-efficacy-focused messaging is most effective at supporting response rates.

INTRODUCTION/BACKGROUND:People with serious mental illness (SMI) have a high smoking prevalence and low quit rates. Few cessation treatments are tested in smokers with SMI. Mental health (MH) providers are reluctant to address smoking. Proactive tobacco cessation treatment strategies reach out directly to smokers to offer counseling and medication and improve treatment utilization and quit rates. The current study is a secondary analysis of a randomized controlled trial of proactive outreach for tobacco cessation treatment in VA MH patients. METHODS:Participants (N=1938, 83% male, mean age 55.7) across 4 recruitment sites, who were current smokers and had a MH visit in the past 12 months, were identified using the electronic medical record. Participants were randomized to Intervention (telephone outreach call plus invitation to engage in MH tailored telephone counseling and assistance obtaining nicotine replacement therapy [NRT]) or Control (usual care). The current study assessed outcomes in participants with SMI (N=982). RESULTS:Compared to the Control group, participants assigned to the Intervention group were more likely to engage in telephone counseling (22% vs. 3%) and use NRT (51% vs. 41%). Participants in the Intervention group were more likely to be abstinent (7-day point prevalence; 18%) at 12 months than participants in the Control group; 11%) but equally likely to make quit attempts. CONCLUSIONS:Proactive tobacco cessation treatment is an effective strategy for tobacco users with SMI. Proactive outreach had a particularly strong effect on counseling utilization. Future randomized clinical trials examining proactive tobacco treatment approaches in SMI treatment settings are needed. IMPLICATIONS/CONCLUSIONS:Few effective treatment models exist for smokers with serious mental illness. Proactive tobacco cessation outreach with connections to mental health tailored telephone counseling and medication promotes tobacco abstinence among smokers with serious mental illness and is an effective treatment strategy for this underserved population.

Background/UNASSIGNED:Smoking remains a major public health burden among persons with opioid and/or alcohol use disorder. Methods/UNASSIGNED:A 49-item semi-structured survey was conducted among urban, inpatient detoxification program patients eliciting demographic and clinical characteristics, smoking profile, technology use patterns, and preferences for adopting technology-based smoking cessation interventions. Multivariate logistic regression models further evaluated the association between participant demographic and clinical characteristics and technology preferences. Results/UNASSIGNED:Participants were mostly male (91%), and admitted for detoxification for alcohol (47%), heroin (31%), or both alcohol and heroin (22%). Past 30-day smoking was reported by 78% of the sample. Mobile phone ownership was common (89%); with an average past-year turnover of 3 mobile phones and 3 phone numbers. Computer ownership was low (28%) and one third reported daily internet use (34%). Telephone (41%) and text message-based interventions (40%) were the most popular platforms to facilitate smoking cessation. Conclusions/UNASSIGNED:Despite concurrent AUD-OUD, most respondents had attempted to quit smoking in the last year and preferred telephone- and text message-based interventions to facilitate smoking cessation. High turnover of mobile phones, phone numbers, and limited access to computers pose barriers to dissemination of technology-based smoking cessation interventions in this vulnerable population.

Importance/UNASSIGNED:The prevalence of the use of electronic cigarettes (e-cigarettes) in the United States has grown rapidly since their introduction to the market more than a decade ago. While several studies have demonstrated an association between combustible cigarette smoking and depression, the association between e-cigarette use and depression has not been thoroughly studied. Objective/UNASSIGNED:To examine the association between e-cigarette use and depression in a nationally representative sample of the adult population in the United States. Design, Setting, and Participants/UNASSIGNED:Cross-sectional study of the Behavioral Risk Factor Surveillance System database, 2016 to 2017. The Behavioral Risk Factor Surveillance System is the largest national telephone-based survey of randomly sampled adults in the United States. A total of 892 394 participants with information on e-cigarette use and depression were included. Data analysis was conducted in May 2019. Exposures/UNASSIGNED:Electronic cigarette use status defined by self-report as never, former, or current use. Main Outcomes and Measures/UNASSIGNED:Self-reported history of a clinical diagnosis of depression. Results/UNASSIGNED:Of the 892 394 participants (414 326 [29.0%] aged ≥60 years; 502 448 [51.3%] women), there were 28 736 (4.4%) current e-cigarette users, of whom 13 071 (62.1%) were aged between 18 and 39 years. Compared with never e-cigarette users, current e-cigarette users were more likely to be single, male, younger than 40 years, and current combustible cigarette smokers (single, 120 797 [24.3%] vs 10 517 [48.4%]; men, 318 970 [46.6%] vs 14 962 [60.1%]; aged 18-39 years, 129 085 [32.2%] vs 13 071 [62.1%]; current combustible cigarette use, 217 895 [7.9%] vs 8823 [51.8%]). In multivariable adjusted models, former e-cigarette users had 1.60-fold (95% CI, 1.54-1.67) higher odds of reporting a history of clinical diagnosis of depression than never users, whereas current e-cigarette users had 2.10 (95% CI, 1.98-2.23) times higher odds. Additionally, higher odds of reporting depression were observed with increased frequency of use among current e-cigarette users compared with never users (daily use: odds ratio, 2.39; 95% CI, 2.19-2.61; occasional use: odds ratio, 1.96; 95% CI, 1.82-2.10). Similar results were seen in subgroup analyses by sex, race/ethnicity, smoking status, and student status. Conclusions and Relevance/UNASSIGNED:This study found a significant cross-sectional association between e-cigarette use and depression, which highlights the need for prospective studies analyzing the longitudinal risk of depression with e-cigarette use. If confirmed by other study designs, the potential mental health consequences may have regulatory implications for novel tobacco products.

BACKGROUND:Research on women with substance use disorders has expanded, yet knowledge and implementation gaps remain. METHODS:Drawing from topics discussed at the 2017 meeting of InWomen's in Montreal, Canada, this article reviews key progress in research on substance use among women, adolescents, and families to delineate priorities for the next generation of research. RESULTS:The field has seen significant accomplishments in multiple domains, including the management of pregnant women with substance use and comorbid psychiatric disorders, caring for neonates in opioid withdrawal, greater inclusion of and treatment options for LGBTQ + communities, gendered instrumentation, and gender-focused HIV interventions for adolescent girls and women. Women who use alcohol and other drugs often experience other comorbid medical conditions (chronic Hepatitis C and HIV), contextual confounders (intimate partner violence exposure, homelessness, trauma), and social expectations (e.g., as caretakers) that must be addressed as part of integrated care to effectively treat women's substance use issues. Although significant advances have been made in the field to date, gender-based issues for women remain a neglected area in much of substance abuse research. Few dedicated and gender-focused funding opportunities exist and research has been siloed, limiting the potential for collaborations or interdisciplinary cross-talk. CONCLUSION:Given renewed attention to substance use in the context of the burgeoning opioid epidemic and shifts in global politics that affect women's substance use, the field requires a strategic rethink to invigorate a pipeline of future research and researchers.