Literature Collection

INTRODUCTION: Prescription drug abuse is a major public health problem in rural and suburban areas of the United States, however its emergence in large urban settings with endemic injection drug use remains understudied. We examined temporal trends in injection drug use initiation and mortality among people who inject drugs (PWID) in Baltimore, Maryland. METHODS: Data were derived from the baseline assessment of PWID enrolled in a community-based cohort study with longitudinal follow-up for mortality assessment. PWID were recruited from 2005-2008 (N = 1,008) and 2015-2018 (N = 737). We compared characteristics by birth cohort (before/after 1980) and type of drug initiated (prescription opioids, prescription non-opioids, non-injection illicit drugs, or injection drugs). We calculated standardized mortality ratios (SMR) using the US general population as the reference. RESULTS: PWID born after 1980 were more likely to initiate drug use with prescription opioids and non-opioids and had higher levels of polysubstance prior to injection initiation, compared to individuals born before 1980. Overall mortality was high: 2.59 per 100 person-years (95% CI: 2.27-2.95 per 100 person-years). Compared to the US population, the highest SMRs were observed among participants between 40-44 years of age, with especially high mortality among women in this age group (SMR:29.89, 95% CI: 15.24-44.54). CONCLUSIONS: Mirroring national trends, the profile of PWID in Baltimore has changed with increased prescription drug abuse and high levels of polysubstance use among younger PWID. Interventions need to reach those using prescription drugs early after initiation of use in order to reduce transition to injecting. Urgent attention is warranted to address premature mortality, particularly among middle-aged and female PWID.

There is undoubtedly an alarmingly rising trend of substance use among older adults. This has necessitated a paradigm shift in healthcare and propelled strategies aimed at effective prevention and screening. Age-related physiological changes, such as diminished metabolism and increased substance sensitivity, make older adults particularly vulnerable to adverse effects of substances. This not only has adverse psychological consequences but also physical consequences like complicating chronic illnesses and harmful interactions with medications, which lead to increased hospitalization. Standard screening tools can identify substance use disorders (SUDs) in older adults. Tools like the Cut-down, Annoyed, Guilty, and Eye-opener (CAGE) questionnaire and Michigan Alcohol Screening Test-Geriatric (MAST-G) are tailored to detect alcoholism, while the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) and Alcohol Use Disorders Identification Test (AUDIT) assess abuse of illicit and prescription drugs. Since older adults are more socially integrated, screening should be done using non-stigmatizing and non-judgmental language. Prevention strategies include educational programs, safe prescribing practices, and prescription drug monitoring. Detection of substance abuse should be followed by brief interventions and specialized referrals. In conclusion, heightened awareness, improved screening, and preventive measures can mitigate substance abuse risks in this demographic. Prioritizing future research on non-addictive pain medications and the long-term effects of substances like marijuana seems justified.

OBJECTIVE: To evaluate trends of attention-deficit/hyperactivity disorder (ADHD) diagnosis rates among children aged 5-17 years over the past decade (2010-2021) and to investigate whether there have been differences in temporal changes based on race and ethnicity, sex, or income. STUDY DESIGN: Childhood ADHD diagnosis was ascertained from electronic health records using International Classification of Diseases ninth revision (314.xx) and International Classification of Diseases tenth revision (F90.x) codes. Data were stratified by child's sex, race and ethnicity, and household income, and rates of ADHD were estimated before and after adjustment for potential confounders. RESULTS: The overall ADHD diagnosis rates increased from 3.5% in 2010 to 4.0% in 2021. ADHD diagnosis was most prevalent among White children (6.1%), then Black (4.6%), Other/multiple (3.7%), Hispanic (3.1%), and Asian/Pacific Islander (PI) (1.7%). ADHD was also highly prevalent among boys (73.3%) or family income≥$70,000 (50.0%). ADHD diagnosis increased among Black (4.2% to 5.1%), Hispanic (2.8% to 3.6%), and Asian/PI children (1.5% to 2.0%) but remained stable for White (6.2% to 6.1%) and Other/multiple race/ethnic children (3.7% to 3.7%). Increases in the prevalence among girls were also observed. CONCLUSION: The prevalence of ADHD in children has risen with the largest increases observed for Black, Hispanic, and Asian/PI children. Rates among less affluent families and girls have also been increasing, narrowing the gaps in diagnosis rates previously observed. These increases may reflect improvements in screening and provision of care among demographics where ADHD has been historically underdiagnosed.

Objectives: Drug overdose (OD) deaths have been increasing over the past 20 years. Although risk factors for drug OD have been identified in adult populations, less is known about risk factors for OD in young people. The aim of this review is to systematically examine the literature to identify risk factors for drug OD specific to young people, including adolescents and young adults. Methods: Our initial PubMed search identified 4001 articles. Included were cross-sectional and longitudinal cohort studies published in English that compared young people who experienced a drug OD to those who did not. Review articles, meta-analyses, case-reports, editorials, epidemiological studies, and qualitative studies were excluded. Two investigators reviewed the full texts of all relevant articles and extracted data on sample demographics, prevalence of OD, and correlates associated with OD. Results: Twelve relevant studies were identified reflective of a sample of 5020 unique individuals with an age range of 14-30 years, and a mean age range of 20.2-26 years. The lifetime prevalence of OD in these young people ranged from 24% to 48%. Substance use characteristics most often associated with OD included injection drug, opioid, and tranquilizer use. Polysubstance use was also found to be strongly associated with OD in three studies. Other replicated risk factors for OD in young people included histories of psychopathology, incarceration, unstable housing, and witnessing an OD. Conclusion: Opioid, tranquilizer, and injection drug use have been identified as risk factors for OD in both younger and older adult populations. Risk factors that emerged as noteworthy predictors of OD in young people specifically include polysubstance use, psychiatric comorbidity, unstable housing, and witnessing an OD. There remains a paucity of literature on drug OD risk factors in young people, with little information regarding medical and treatment history risk factors.

IMPORTANCE: While a diverse array of cannabis products that may appeal to youth is currently available, it is unknown whether the risk of persistent cannabis use and progression to higher frequency of use after experimentation differs among cannabis products. OBJECTIVE: To estimate the comparative relative risk of experimental use of 5 cannabis products on use status and frequency of use among adolescents during 12 months of follow-up. DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, data were collected from 3065 adolescents at 10 high schools in southern California, with baseline data collected in spring 2016, when students were in 11th grade, and 6-month and 12-month follow-up surveys collected in fall 2016 and spring 2017, when students were in 12th grade. Analyses, conducted from April to June 2019, were restricted to 2685 participants who were light or nonusers of any cannabis product (ie, ≤2 days in the past 30 days) at baseline. EXPOSURES: Number of days of use of each cannabis product (ie, combustible, blunts, vaporized, edible, or concentrated) in the past 30 days at baseline (ie, 1-2 vs 0 days). MAIN OUTCOMES AND MEASURES: Past 6-month use (ie, yes vs no) and number of days of use in the past 30 days at 6-month and 12-month follow-ups for each product. RESULTS: Of 2685 individuals in the analytic sample, 1477 (55.0%) were young women, the mean (SD) age was 17.1 (0.4) years, and a plurality (1231 [46.6%]) were Hispanic individuals. Among them, 158 (5.9%) reported combustible cannabis use on 1 to 2 days of the past 30 days at baseline, 90 (3.4%) reported blunt use, 78 (2.9%) reported edible cannabis use, 17 (0.6%) reported vaping cannabis, and 15 (0.6%) reported using cannabis concentrates. In regression models adjusting for demographic characteristics and poly-cannabis product use, statistically stronger associations of baseline use with subsequent past 6-month use at the 6-month and 12-month follow-ups were observed for combustible cannabis use (odds ratio, 6.01; 95% CI, 3.66-9.85) and cannabis concentrate use (odds ratio, 5.87; 95% CI, 1.18-23.80) compared with use of blunts (OR, 2.77; 95% CI, 1.45-5.29) or edible cannabis (OR, 3.32; 95% CI, 1.86-5.95) (P for comparison < .05); vaporized cannabis use (OR, 5.34; 95% CI, 1.51-11.20) was not significantly different from the other products. In similarly adjusted models, we found the association of cannabis use at baseline with mean days of use at the 6-month and 12-month follow-ups was significantly stronger for cannabis concentrate than for other cannabis products; participants who had used cannabis concentrate on 1 to 2 of the past 30 days at baseline (vs 0 days) used cannabis concentrate a mean of 9.42 (95% CI, 2.02-35.50) more days in the past 30 days at the 6-month and 12-month follow-ups (P for comparison < .05). CONCLUSIONS AND RELEVANCE: Cannabis control efforts should consider targeting specific cannabis products, including combustible cannabis and cannabis concentrate, for maximum public health consequences.