Faculty Bibliography

OBJECTIVE:Suicidal behavior and bullying victimization are important indicators of adolescent psychological distress, and are patterned by sex, race/ethnicity and sexual identity. This study aimed to estimate trends and disparities in these factors along key demographics. METHOD/METHODS:Youth Risk Behavior Survey data (2015-2019, N=44,066) were collected biennially through national cross-sectional surveys of US school-attending adolescents. Survey-weighted logistic regressions examined disparities in past-year bullying and suicidal behavior, overall and by demographics. RESULTS:Bullying in 2019 was highest for female (vs. male) students (OR=1.82, 95% CI:[1.62, 2.06]), American Indian/Alaskan Native (vs White) students (OR= 1.48, [0.91, 2.41], p>.05), and gay/lesbian (vs heterosexual) students (OR= 2.81, [2.07, 3.81]). Suicidal behavior disparities affected similar groups. There was minimal evidence for shifts in disparities since 2015, with the exception of bullying for gay/lesbian adolescents. The prevalence of bullying victimization among gay and lesbian adolescents went from 31.6% to 44.5% between 2015 and 2019, surpassing the bisexual and "Not Sure" groups to be the sexual identity group with the highest rate of bullying victimization. CONCLUSION/CONCLUSIONS:Interventions that operate on multiple structural levels and empower marginalized youth are needed.

BACKGROUND:Mandates for prescriber use of prescription drug monitoring programs (PDMPs), databases tracking controlled substance prescriptions, are associated with reduced opioid analgesic (OA) prescribing but may contribute to care discontinuity and chronic opioid therapy (COT) cycling, or multiple initiations and terminations. OBJECTIVE:To estimate risks of COT cycling in New York City (NYC) due to the New York State (NYS) PDMP mandate, compared to risks in neighboring New Jersey (NJ) counties. DESIGN/METHODS:We estimated cycling risk using Prentice, Williams, and Peterson gap-time models adjusted for age, sex, OA dose, payment type, and county population density, using a life-table difference-in-differences design. Failure time was duration between cycles. In a subgroup analysis, we estimated risk among patients receiving high-dose prescriptions. Sensitivity analyses tested robustness to cycle volume considering only first cycles using Cox proportional hazard models. PARTICIPANTS/METHODS:The cohort included 7604 patients dispensed 12,695 prescriptions. INTERVENTIONS/METHODS:The exposure was the August 2013 enactment of the NYS PDMP prescriber use mandate. MAIN MEASURES/METHODS:We used monthly, patient-level data on OA prescriptions dispensed in NYC and NJ between August 2011 and July 2015. We defined COT as three sequential months of prescriptions, permitting 1-month gaps. We defined recurrence as re-initiation of COT after at least 2 months without prescriptions. The exposure was enactment of the PDMP mandate in NYC; NJ was unexposed. KEY RESULTS/RESULTS:Enactment of the NYS PDMP mandate was associated with an adjusted hazard ratio (HR) for cycling of 1.01 (95% CI, 0.94-1.08) in NYC. For high-dose prescriptions, the risk was 1.16 (95% CI, 1.01-1.34). Sensitivity analyses estimated an overall risk of 1.01 (95% CI, 0.94-1.11) and high-dose risk of 1.09 (95% CI, 0.91-1.31). CONCLUSIONS:The PDMP mandate had no overall effect on COT cycling in NYC but increased cycling risk among patients receiving high-dose opioid prescriptions by 16%, highlighting care discontinuity.

BACKGROUND/UNASSIGNED:Nicotine vaping among U.S. adolescents has risen rapidly over the past decade, particularly for youth in grade 12. While previous studies examined the relationship between nicotine vaping and combustible cigarette use, less is known about the co-occurrence between vaping and other tobacco products. METHODS/UNASSIGNED:Using Monitoring the Future grade 12 data (2017-2019), we investigated associations between past 30-day nicotine vaping and non-vaping, non-cigarette tobacco use (smokeless tobacco, large cigars, cigarillos, hookah). Population prevalences of four categories were assessed: neither, vaping only, non-vaping of non-cigarette tobacco only, or both. We further investigated these relationships with logistic regressions accounting for the complex survey design (unadjusted, demographic-adjusted, and further adjusted for other substance use). Finally, analyses were stratified by combustible cigarette use. RESULTS/UNASSIGNED:Depending on the non-cigarette tobacco product, 2.5% to 5.4% of grade 12 students vaped nicotine and used a non-cigarette tobacco product. Controlling for demographics, cigarillo use was associated with nicotine vaping (adjusted RR = 3.44, 95% CI: 3.08, 3.84), as was hookah use (aRR = 3.51, 95% CI: 2.92, 4.23), smokeless tobacco (aRR = 2.97, 95% CI: 2.51, 3.52), and cigar use (aRR = 2.90, 95% CI: 2.49, 3.37). Controlling for cannabis and all non-cigarette tobacco products simultaneously attenuated associations. Associations were stronger among students who did not use cigarettes. DISCUSSION/UNASSIGNED:Nicotine vaping is associated with use of many non-cigarette tobacco products, including smokeless tobacco, cigarillos, cigars, and hookah. As prevalence of nicotine vaping remains high among adolescents, we should monitor co-use of vaping and other tobacco products.

IMPORTANCE:Benzodiazepines are prescribed for the treatment of adolescent sleep disorders; however, benzodiazepine overdoses occur, often in combination with opioids. OBJECTIVE:To evaluate whether benzodiazepine treatment for sleep disorders, compared with alternative pharmacologic treatments (trazodone, hydroxyzine, zolpidem, zaleplon, and eszopiclone), is associated with increased risk of drug overdose for young people. DESIGN, SETTING, AND PARTICIPANTS:This cohort study included privately insured people 10 to 29 years of age identified from a US commercial claims database (MarketScan), from January 1, 2009, to December 31, 2018. Young people with a sleep disorder diagnosis initiating benzodiazepine (n = 23 084) or comparator pharmacologic treatments (n = 66 706) were included in the study. Statistical analysis was performed from November 1, 2021, to May 16, 2022. EXPOSURES:New use of benzodiazepine treatment or comparator pharmacologic treatments (defined as ≥1 year without a prescription for benzodiazepine or comparator medications). MAIN OUTCOMES AND MEASURES:Incident diagnosed drug overdoses were identified from inpatient and emergency department records within 6 months of treatment initiation. The propensity score-adjusted cumulative incidence of overdose and hazard ratios (HRs) were estimated with intention-to-treat (analyzed based on initial treatment) and as-treated analyses (added censoring at treatment discontinuation). Results were stratified by prior prescription opioid fill. RESULTS:The cohort included 23 084 young people initiating benzodiazepine treatment (14 444 female participants [62.6%]; mean [SD] age, 23 [4.1] years) and 66 706 initiating a comparator treatment (38 446 female participants [57.6%]; mean [SD] age, 22 [4.4] years). Six months after treatment initiation, 9.7% (95% CI, 9.3%-10.1%) of benzodiazepine users and 12.3% (95% CI, 12.1%-12.6%) of the comparator group were still receiving treatment. The crude incidence of drug overdose at 6 months was 0.9% for benzodiazepine initiators and 0.8% for comparator treatment initiators. In adjusted analyses, an increased risk of drug overdose was associated with benzodiazepines vs comparator treatments (intention-to-treat analysis: HR, 1.25 [95% CI, 1.03-1.51]; as-treated analysis: HR, 1.44 [95% CI, 1.14-1.80]). This association was stronger among young people with a recent prescription opioid fill vs those without a recent prescription opioid fill (as-treated analysis: adjusted HR, 2.01 [95% CI, 1.24-3.25] vs adjusted HR, 1.31 [95% CI, 1.00-1.70]). CONCLUSIONS AND RELEVANCE:The findings of this study suggest that benzodiazepines, compared with alternative pharmacologic treatments for common sleep disorders, were associated with an increased risk of drug overdose among young people during the following 6-month period, especially among those with a recent opioid prescription. Drug overdose is an important safety consideration when treating young people with benzodiazepines.

BACKGROUND AND AIMS/OBJECTIVE:In 2013, Uruguay became the first country to legalize and regulate the production and distribution of cannabis for recreational use. We measured whether Uruguay's non-commercial model of recreational cannabis legalization was associated with changes in the prevalence of risky and frequent cannabis use among secondary school students. DESIGN/METHODS:We used data from repeated cross-sectional surveys of secondary students in Uruguay and Chile (2007-2018). Using a difference-in-difference approach, we evaluated changes in the prevalence of past-year, past-month, any risky and frequent cannabis use following enactment (2014) and implementation (2016) of cannabis legalization among the full sample of secondary students and among students who reported past-year/month use. We examined changes separately for students aged 12-17, and students for whom cannabis became legally accessible, ages 18-21. SETTING/METHODS:Uruguay and Chile (2007-2018). PARTICIPANTS/METHODS:grade (n=204,730). MEASUREMENTS/METHODS:Past-year and past-month cannabis use; any risky cannabis use measured with the Cannabis Abuse Screening Test (CAST); and frequent cannabis use (10+ days in the past-month). FINDINGS/RESULTS:We found a decrease in past-year and past-month use following enactment or implementation. Among students ages 18-21, post-enactment, we observed a transitory increase in 2014 that decreased thereafter for: any risky use among those who reported past-year use (prevalence difference [PD]=13.5%; 95% confidence interval [CI]: 2.0, 24.9), frequent use in the full sample (PD=4.5%; 95%CI: 1.0, 8.1), and frequent use among those who reported past-month use (PD=16.8%; 95%CI: 1.9, 31.8). CONCLUSION/CONCLUSIONS:The legalization of recreational cannabis in Uruguay was not associated with overall increases in either past-year/past-month cannabis use or with multi-year changes in any risky and frequent cannabis use among young people.

Overdose Good Samaritan Laws (GSLs) aim to reduce mortality by providing limited legal protections when an overdose bystander summons help. Most research into the impact of these laws is dated or potentially confounded by co-enacted naloxone access laws. Lack of awareness and trust in GSL protections, as well as fear of police involvement and legal repercussions, remain key deterrents of help-seeking. These barriers may be unequally distributed by race due to racist policing and drug policies, potentially producing racial disparities in the effectiveness of GSLs for reducing overdose mortality. We used 2015-2019 vital statistics data to estimate the effect of recent GSLs on overdose mortality, overall (eight states) and by Black/white race (four states). Given GSLs' near ubiquity, few unexposed states were available for comparison. We therefore proposed an "inverted" synthetic control method (SCM) to compare overdose mortality in new-GSL states to states with GSLs throughout the analytic period. The estimated relationships between GSLs and overdose mortality, both overall and stratified by Black/white race, were consistent with chance. An absence of effect could result from insufficient protection provided by the laws, insufficient awareness of them, and/or reticence to summon help not addressable by legal protections. The inverted SCM may be useful for evaluating other widespread policies.

Former industrial cities facing economic challenges and depopulation often experience high levels of firearm and other forms of violence. Within these cities, violent crime often clusters in neighborhoods affected by high levels of vacant and abandoned housing. This study estimates the effects of building demolition in Detroit, Michigan on the subsequent risk of violent crime using property-level data and longitudinal targeted maximum likelihood estimation. The primary outcome is violent Crime Index crimes (homicide, rape, robbery and aggravated assault). We estimate effects for this category of crimes as a whole and for the subset involving firearms. Drug and other lower-level crimes are included as secondary outcomes. We compare the risk of experiencing each crime type following building demolition in Census blocks and block groups to an estimate of the risk had there been no demolition in the 1-3 quarters prior in 2017. There were >2600 total demolitions in about 1700 blocks in 2017 in Detroit. Nearly all demolished buildings were sourced from tax foreclosures. Estimates suggest the risk for all crime types tested would have been statistically indistinguishable from the observed crime risk had demolitions in the prior 1-3 quarters of 2017 not occurred. Our results run counter to most previous research on this topic, which tends to show a protective effect of demolition on violent crime. Understanding why our results differ may provide important insights into the types of demolition programs with the greatest potential to reduce violent crime.