Search

ObjectiveIn 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 (

BackgroundPrevalence of fentanyl-laced counterfeit prescription pills has been increasing in the US, possibly placing a wider population at risk for unintentional exposure. We aimed to determine whether there have been shifts in the number of fentanyl seizures and in the form of fentanyl seized in the US.MethodsWe examined quarterly national seizure data from High Intensity Drug Trafficking Areas to determine the number of drug seizures in the US containing fentanyl from January 2018 through December 2021. Generalized additive models were used to estimate trends in the number and weight of pill and powder seizures containing fentanyl.ResultsThere was an increase both in the number of fentanyl-containing powder seizures (from 424 in 2018 Quarter 1 [Q1] to 1539 in 2021 Quarter 4 [Q4], β = 0.94, p

BackgroundSubstance use disorders (SUD) elevate the risk for COVID-19 hospitalization, but studies are inconsistent on the relationship of SUD to COVID-19 mortality.MethodsVeterans Health Administration (VHA) patients treated in 2019 and evaluated in 2020 for COVID-19 (n=5,556,315), of whom 62,303 (1.1%) tested positive for COVID-19 (COVID-19+). Outcomes were COVID-19+ by 11/01/20, hospitalization, ICU admission, or death within 60 days of a positive test. Main predictors were any ICD-10-CM SUDs, with substance-specific SUDs (cannabis, cocaine, opioid, stimulant, sedative) explored individually. Logistic regression produced unadjusted and covariate-adjusted odds ratios (OR; aOR).ResultsAmong COVID-19+ patients, 19.25% were hospitalized, 7.71% admitted to ICU, and 5.84% died. In unadjusted models, any SUD and all substance-specific SUDs except cannabis use disorder were associated with COVID-19+(ORs=1.06-1.85); adjusted models produced similar results. Any SUD and all substance-specific SUDs were associated with hospitalization (aORs: 1.24-1.91). Any SUD, cocaine and opioid disorder were associated with ICU admission in unadjusted but not adjusted models. Any SUD, cannabis, cocaine, and stimulant disorders were inversely associated with mortality in unadjusted models (OR=0.27-0.46). After adjustment, associations with mortality were no longer significant. In ad hoc analyses, adjusted odds of mortality were lower among the 49.9% of COVID-19+ patients with SUD who had SUD treatment in 2019, but not among those without such treatment.ConclusionsIn VHA patients, SUDs are associated with COVID-19 hospitalization but not COVID-19 mortality. SUD treatment may provide closer monitoring of care, ensuring that these patients received needed medical attention, enabling them to ultimately survive serious illness.

ObjectiveThe Department of Veterans Affairs' (VA) electronic health records (EHR) offer a rich source of big data to study medical and health care questions, but patient eligibility and preferences may limit generalizability of findings. We therefore examined the representativeness of VA veterans by comparing veterans using VA healthcare services to those who do not.MethodsWe analyzed data on 3051 veteran participants age ≥ 18 years in the 2019 National Health Interview Survey. Weighted logistic regression was used to model participant characteristics, health conditions, pain, and self-reported health by past year VA healthcare use and generate predicted marginal prevalences, which were used to calculate Cohen's d of group differences in absolute risk by past-year VA healthcare use.ResultsAmong veterans, 30.4% had past-year VA healthcare use. Veterans with lower income and members of racial/ethnic minority groups were more likely to report past-year VA healthcare use. Health conditions overrepresented in past-year VA healthcare users included chronic medical conditions (80.6% vs. 69.4%, d = 0.36), pain (78.9% vs. 65.9%; d = 0.35), mental distress (11.6% vs. 5.9%; d = 0.47), anxiety (10.8% vs. 4.1%; d = 0.67), and fair/poor self-reported health (27.9% vs. 18.0%; d = 0.40).ConclusionsHeterogeneity in veteran sociodemographic and health characteristics was observed by past-year VA healthcare use. Researchers working with VA EHR data should consider how the patient selection process may relate to the exposures and outcomes under study. Statistical reweighting may be needed to generalize risk estimates from the VA EHR data to the overall veteran population.

BackgroundFirearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the impact of high-risk (disqualification) and population-based (price increase) approaches on firearm homicide in New York City (NYC).MethodsWe simulated 800,000 agents reflecting a 15% sample of the adult population of NYC. Three groups were considered and disqualified from all firearm ownership for five years, grouped based on prevalence: low prevalence (psychiatric hospitalization, alcohol-related misdemeanor and felony convictions, 0.23%); moderate prevalence (drug misdemeanor convictions, domestic violence restraining orders, 1.03%); and high prevalence (all other felony/misdemeanor convictions, 2.30%). Population-level firearm ownership was impacted by increasing the price of firearms, assuming 1% price elasticity.ResultsIn this hypothetical scenario, to reduce firearm homicide by 5% in NYC, 25% of the moderate prevalence group, or 12% of the high prevalence group needed to be effectively disqualified; even when all of the low prevalence group was disqualified, homicide did not decrease by 5%. An 18% increase in price similarly reduced firearm homicide by 5.37% (95% CI 4.43-6.31%). Firearm homicide declined monotonically as the proportion of disqualified individuals increased and/or price increased. A combined intervention that both increased price and effectively disqualified "high-risk" groups achieved approximately double the reduction in homicide as any one intervention alone. Increasing illegal firearm ownership by 20%, a hypothetical response to price increases, did not meaningfully change results.ConclusionA key takeaway of our study is that adopting high-risk versus population-based approaches should not be an "either-or" question. When individual risk is variable and diffuse in the population, "high-risk approaches" to firearm violence need to focus on relatively prevalent groups and be highly efficacious in disarming people at elevated risk to achieve meaningful reductions in firearm homicide, though countering issues of social justice and stigma should be carefully considered. Similar reductions can be achieved with population-based approaches, such as price increases, albeit with fewer such countering issues.

Background: Being bullied online is associated with being bullied in school. However, links between online bullying and violence-related experiences are minimally understood. We evaluated potential disparities in these associations to illuminate opportunities to reduce school-based violence. Methods: We used five cohorts of Youth Risk Behavior Survey national cross-sectional data (2011-2019, N[subscript total] = 73 074). We used survey-weighted logistic and multinomial models to examine links between online bullying and five school-based violence-related experiences: offline bullying, weapon carrying, avoiding school due to feeling unsafe, being threatened/injured with a weapon, and physical fighting. We examined interactions by sex, race/ethnicity, and sexual identity. Results: Being bullied online was positively associated with all offline violence-related behaviors. Groups with stronger associations between online bullying and physical fighting, including boys, adolescents whose sexual identity was gay/lesbian or unsure, and many adolescents of color (Black, Hispanic/Latino, and Asian/Pacific Islander adolescents), had stronger associations between online bullying and either weapon carrying or avoiding school. Conclusions: Online bullying is not an isolated harmful experience; many marginalized adolescents who experience online bullying are more likely to be targeted in school, feel unsafe, get in fights, and carry weapons. Reduction of online bullying should be prioritized as part of a comprehensive school-based violence prevention strategy.

PurposeDepression is increasingly common among US adolescents; the extent to which social media exposure contributes to this increase remains controversial.MethodsWe used Monitoring the Future data from 8th and 10th grade students (n = 74,472), 2009-2017, to assess the relationship between daily social media use and depressive symptoms. Self-reported depressive symptom score (range: 4-20) was assessed continuously using a log-transformed outcome and at varying cut scores with logistic regression analyses. First, these outcomes were examined overall, comparing adolescents using social media daily to adolescents who were not. We then estimated predicted depressive symptom scores using 26 predictors in order to establish underlying depression risk. We partitioned students into depression risk quintiles to control for confounding due to underlying depression risk and examine heterogeneity in the association between social media use and depressive symptoms. Sensitivity analyses were used to test the robustness of results with different configurations of the predicted score model, and overall associations were examined in two-year groups to identify differences in effects.ResultsFor girls, in adjusted risk-stratified analysis, daily social media use was not associated with high (vs. low) depressive symptoms. For boys, results were inconsistent, suggesting a protective effect of daily social media use at some cut scores. Results were consistent across sensitivity analyses, and any potential harmful effects appear to be limited to 2009-2010, limiting the evidence supporting social media as a current risk factor for depressive symptoms.ConclusionsAmong US adolescents, daily social media use is not a strong or consistent risk factor for depressive symptoms.

Although historically cisgender women (i.e., women whose sex assigned at birth is consonant with their gender) in the United States have had lower levels of alcohol consumption than cisgender men, [...]

Sexual minority adolescents have worse sleep health than their peers. Adolescents who identify as heterosexual and report prior same-sex sexual contact (termed 'discordant heterosexuals') have elevated health risks, but little is known about this group's sleep health. This study examined 2015-2017 Youth Risk Behavior Survey data (n = 12,773 high school students) comparing discordant heterosexuals to their concordant (i.e. sexual identity is concordant with reported sex of sexual contact) heterosexual, bisexual, gay and lesbian peers on three sleep outcomes: sufficient ([greater than or equal to]8 hours), short ([less than or equal to]6 hours) and extremely limited sleep ([less than or equal to]4 hours). Both discordant heterosexual (aOR:0.64, 95% CI:0.47, 0.86) and bisexual students (aOR:0.69, CI:0.56, 0.85) had lower odds of sufficient sleep compared to concordant heterosexuals, even after adjustment for demographic factors and substance use. Discordant heterosexual (aOR:1.29, CI:1.01, 1.66) and bisexual (aOR:1.74, CI:1.54, 1.98) students have higher odds of short sleep. Discordant heterosexual (aOR:1.94, CI:1.36, 2.77) and bisexual students (aOR:2.72, CI:2.23, 3.31) also had higher odds of extremely limited sleep. Victimization may partially explain some of these associations. Sleep health is one factor that may drive health disparities, and efforts to ensure that adolescents are safe and secure in sexual behavior and identity is important to reducing these disparities.

PurposeThe purpose of this study was to estimate the effect of firearm involvement during violent victimization on the level of distress experienced and daily functioning within sociodemographic subgroups.MethodsWe used cross-sectional data from the National Crime Victimization Survey (n = 5698) and Targeted Maximum Likelihood Estimation. Sociodemographic subgroups were defined by age, race, sex, and socioeconomic position. Outcomes included experiencing the victimization as severely distressing and problems in the workplace or at school, or with peers or family.ResultsAmong people victimized with a firearm, nearly 40% experienced the victimization as severely distressing and 28% reported daily functioning problems as a result of the victimization, compared with 25% and 27% of those victimized without a firearm. In most of the subgroups examined, a greater proportion of people described the event as severely distressing when a firearm was involved in the victimization, ranging up to 19 percentage points higher among women and among black respondents (95% CI for women = 10%-28%; for blacks = 6%-31%).ConclusionsOur findings suggest an almost universal negative response to firearm involvement during a violent victimization as compared with violent victimizations involving other or no weapons. These findings highlight the need for efforts by medical and mental health practitioners to address the potential sequelae of experiencing severe distress during a firearm victimization.

Alexander Tsai and co-authors discuss the role of stigma in responses to the US opioid crisis.

Increasing alcohol outlet density is well-documented to be associated with increased alcohol use and problems, leading to the policy recommendation that limiting outlet density will decrease alcohol problems. Yet few studies of decreasing problematic outlets and outlet density have been conducted. We estimated the association between closing alcohol outlets and alcohol use and alcohol-related violence, using an agent-based model of the adult population in New York City. The model was calibrated according to the empirical distribution of the parameters across the city's population, including the density of on- and off-premise alcohol outlets. Interventions capped the alcohol outlet distribution at the 90th to the 50th percentiles of the New York City density, and closed 5% to 25% of outlets with the highest levels of violence. Capping density led to a lower population of light drinkers (42.2% at baseline vs. 38.1% at the 50th percentile), while heavy drinking increased slightly (12.0% at baseline vs. 12.5% at the 50th percentile). Alcohol-related homicides and nonfatal violence remained unchanged. Closing the most violent outlets was not associated with changes in alcohol use or related problems. Results suggest that focusing solely on closing alcohol outlets might not be an effective strategy to reduce alcohol-related problems.

BackgroundPrescription opioid overdose (POD) and heroin overdose (HOD) rates have quadrupled since 1999. Community-level socioeconomic characteristics are associated with opioid overdoses, but whether this varies by urbanicity is unknown.MethodsIn this serial cross-sectional study of zip codes in 17 states, 2002-2014 (n = 145,241 space-time units), we used hierarchical Bayesian Poisson space-time models to analyze the association between zip code-level socioeconomic features (poverty, unemployment, educational attainment, and income) and counts of POD or HOD hospital discharges. We tested multiplicative interactions between each socioeconomic feature and zip code urbanicity measured with Rural-Urban Commuting Area codes.ResultsPercent in poverty and of adults with ≤ high school education were associated with higher POD rates (Rate Ratio [RR], 5% poverty: 1.07 [95% credible interval: 1.06-1.07]; 5% low education: 1.02 [1.02-1.03]), while median household income was associated with lower rates (RR, $10,000: 0.88 [0.87-0.89]). Urbanicity modified the association between socioeconomic features and HOD. Poverty and unemployment were associated with increased HOD in metropolitan areas (RR, 5% poverty: 1.12 [1.11-1.13]; 5% unemployment: 1.04 [1.02-1.05]), and median household income was associated with decreased HOD (RR, $10,000: 0.88 [0.87-0.90]). In rural areas, low educational attainment alone was associated with HOD (RR, 5%: 1.09 [1.02-1.16]).ConclusionsRegardless of urbanicity, elevated rates of POD were found in more economically disadvantaged zip codes. Economic disadvantage played a larger role in HOD in urban than rural areas, suggesting rural HOD rates may have alternative drivers. Identifying social determinants of opioid overdoses is particularly important for creating effective population-level interventions.