Driving under the influence of cannabis is a significant public health concern that is particularly common in young adults (aged 18–25 years) and has increased in recent years. Vaping has also ...dramatically increased, particularly among young populations, and is frequently used for cannabis administration among young adults. Therefore, this study aimed to examine the positive association between vaping and cannabis driving under the influence among young adults (aged 18–25 years).
This study used the 2020 National Survey on Drug Use and Health and included young adults aged 18–25 years. This study examined past-year cannabis driving under the influence prevalence by past-year vaping at the intersection of past-year cannabis use, after adjusting for other associated factors such as race/ethnicity, sex, employment status, past-year other tobacco use, past-year serious psychological distress, and past-year driving under the influence of alcohol. Data were analyzed in 2022.
Among a sample of 7,860 U.S. individuals aged 18–25 years, 23.8% vaped in the past year, and 9.7% reported past-year cannabis driving under the influence. Past-year vaping was positively associated with past-year cannabis use (adjusted prevalence ratio=2.12; 95% CI=1.91, 2.35). Among those with cannabis use in the past year, past-year vaping was positively associated with past-year cannabis driving under the influence (adjusted prevalence ratio=1.52; 95% CI=1.25, 1.84).
This study found positive associations between past-year vaping, cannabis use, and cannabis driving under the influence among U.S. young adults, indicating that vaping was positively associated with cannabis use. Vaping was also positively associated with cannabis driving under the influence among those who used cannabis. This preliminary evidence could inform prevention/intervention strategies related to vaping and cannabis driving under the influence.
The prevalence of anxiety disorders, and mental chronic diseases, has increased over the last decade among adolescents. Since aerobic exercise reduces the risk of chronic diseases and stress ...symptoms, we aimed to examine the association between aerobic exercise in adolescence and anxiety disorders in adulthood.
Self-reported, publicly available data from 5,114 adolescents who participated in Waves I and IV of the National Longitudinal Study of Adolescent Health (Add Health) was analyzed from 1994-2009. We included US-based individuals aged 16 years on average and observed them for 15 years. Weighted Poisson regression models estimated the association between aerobic exercise in Wave I (1994, baseline) and anxiety disorders in Wave IV (2009, adulthood), adjusting for sociodemographic characteristics and substance use at baseline.
Overall, 639/5,114 (weighted 12.96%) individuals experienced anxiety disorders at baseline. Age and sex differed significantly across all exercise groups (p's<0.001). Aerobic exercise did not significantly protect against anxiety disorders in adulthood: compared to adolescents who did not exercise at all, those who exercised 1-2 times/week had 0.85 times the prevalence of anxiety disorders during adulthood (95% CI = 0.65, 1.12; p = 0.25). Those who exercised 3-4 times/week had 0.81 times the prevalence (95% CI = 0.61, 1.08, p = 0.15) and those who exercised 5+ times/week had 0.84 times the prevalence (95% CI = 0.63, 1.13, p = 0.25) than those who did not exercise at all.
Aerobic Exercise in adolescence did not protect against anxiety disorders in adulthood. More evidence is needed on this association, including using homogeneous measures of exercise and repeated measures methods.
•From 2004 to 2017, less than 1% of US reproductive age women have used heroin in the past 30 days.•Heroin use prevalence has increased over time among non-pregnant women.•Similar increase was not ...observed among pregnant women.
Opioid use during pregnancy has been linked to several adverse outcomes including stillbirth, preterm birth and neonatal abstinence syndrome. Recent data suggest that heroin use has increased in the United States (US) whereas prescription opioid use has decreased. Prevalence estimates for reproductive age women combine heroin and non-medical prescription opioid use, which might mask the increasing heroin trend. The aim of the current study is to estimate the prevalence of heroin use among US women of reproductive age, stratified by pregnancy status. For each year, a representative sample of the US civilian non-institutionalized population is recruited for the National Survey on Drug Use and Health (NSDUH). Pregnancy status and heroin use were assessed in women 15–44 years of age (n = 277,333) using audio computerized-assisted self-interviews. From 2004 to 2017, the prevalence of past 30-day heroin use was 12 per 10,000 reproductive age women (95% confidence interval CI = 11, 14). Heroin use has increased from 6 per 10,000 women in 2004–05 to 18 per 10,000 women in 2016–17 (Average percent change = 20.8; 95% 11.2, 31.2). The increase was evident among non-pregnant women, but not among pregnant women. Heroin use remains uncommon among women of reproductive age, yet its prevalence has increased over time. Screening for heroin use might be needed at multiple time points including prior to pregnancy to mitigate adverse outcomes associated with use during pregnancy.
Background: While prescription psychotherapeutic drug use (PPDU) and nicotine use pose substantial problems in isolation, they pose an increased risk in combination. This study aimed to estimate the ...prevalence of PPDU for young people, stratified by nicotine use status. A trend analysis was used to examine changes in PPDU and nicotine use over time. Methods: We used a cross-sectional population-based sample of young people aged 16-25 years (n = 10,454) from the National Health and Nutrition Examination Survey (NHANES, 2003-2018). For each data cycle, the prevalence of self-reported PPDU and nicotine including pain relievers, sedatives, stimulants, and tranquilizers was estimated. Using Joinpoint regression, we tested for significant changes in trends using a log-linear model and permutation test approach and produced the average data cycle percentage change (ADCPC). Results: From 2003 to 2018, 6.7% of young people had PPDU and 27.3% used nicotine. The prevalence of cigarette smoking decreased while other nicotine product use increased (p's < 0.001). Those who used nicotine were more likely to have PPDU (8.2%; 95% CI = 6.5%, 9.8%) vs. non-nicotine use (6.1%; 95% CI = 5.1%, 7.0%; p = 0.01). Results indicated a decreasing trend for nicotine use (ADCPC = −3.8, 95% CI = −7.2, −0.3; p = 0.04), but not for PPDU (ADCPC = 1.3; 95% CI = −4.7, 7.8; p = 0.61). On further examination, opioid use decreased, sedative use remained stable, and stimulant and tranquilizer use increased over time. Conclusions: From 2003 to 2018, young people who used nicotine had a higher prevalence of PPDU than those who did not. Clinicians should communicate the association between nicotine use and prescription drugs when prescribing or managing young patients' medications.
The peak risk of first extramedical use of prescription pain relievers (PPRs) is in mid-adolescence, often after underage drinking has begun. This research aims to investigate discrete classes of ...similar young people based on their newly incident extramedical use of PPR and alcohol involvement, with empirical evaluation of the underlying structure of identified subgroups and their epidemiological distributions in the United States. The U.S. National Surveys on Drug Use and Health, 2002-2013, sampled, recruited, and assessed 24,789 newly incident extramedical PPR users ages 12-20 years, with self-interviews on PPR, alcohol, and covariates. Latent classes of persistence were formed using PPR and alcohol status variables. Then, age and sex were studied as potentially important predictors of class membership. Analysis-weighted estimates and delta method variances were derived. Three classes were distinguished by extramedical PPR and alcohol use patterns: (a) nonpersistent (79%), (b) intermittent (15%), and (c) persistent (6%). There were no differences across classes by age, but being female was associated with greater odds of being in the intermittent class or persistent class compared to the nonpersistent class. Presenting clinical features of alcohol and/or opioid dependence that have become manifest at or near time of first PPR use can be indicators of persisting in extramedical use of PPR, particularly for young people who have recently started extramedical PPR use. Persistent adolescent and young adult extramedical PPR users require tailored public health prevention and intervention strategies based on their vulnerability to continue use over time.
Public Health Significance
Based on their recent alcohol and opioid involvement, this study suggests that there are distinct subgroups of 12- to 20-year-olds who have just begun to use prescription pain relievers outside a prescriber's intent. Screening for alcohol and prescription pain reliever use before prescribing opioids in the primary care setting may be an integral step in beginning to address a persistent opioid problem or preventing one from beginning.
Kratom, an herbal substance with stimulant and opioid-like effects commonly used in capsules or powder to be ingested or brewed as a tea, has been gaining popularity in the United States (US). US ...e-cigarette use (i.e., vaping) has exponentially increased in recent years. Given the potential risks of kratom (e.g., poisonings) and the increasing prevalence of e-cigarette use, understanding the association between them is important to inform prevention strategies and regulatory policies. We harnessed data from the 2020 National Survey on Drug Use and Health (NSDUH; n = 27,170) to examine past-year kratom use by past-year e-cigarette use among adults. We ran a logistic regression model on kratom use by e-cigarette use adjusting for associated factors with substance use. Among all respondents, the estimated prevalence of past-year kratom use was 0.9% and an estimated 9.7% reported past-year e-cigarette use. Our multivariable model found those with e-cigarette use (vs. not) had 4.80 higher odds of using kratom in the past year (aOR = 4.80; 95% CI = 2.62, 8.80). These findings might help inform the need for continuing education for physicians and healthcare providers related to practice in managing patients with kratom use, future studies for regulatory policies on e-cigarettes (e.g., e-liquids), or other FDA policies related to kratom.
•Approximately, 0.9% (2,062,313 US adults) reported past-year kratom use in 2020.•Individuals with e-cigarette use (vs. not) showed 4.80 higher odds of using kratom.•Continuing education for healthcare providers related to kratom use is warranted.•More research is needed for regulatory policies related to e-cigarettes and kratom.
•We examined smoking quit ratios by opioid misuse and opioid use disorder (OUD).•Smoking prevalence was higher for persons with OUD and opioid misuse vs. without.•Smoking quit ratios were lower for ...persons with OUD and opioid misuse vs. without.•Quit ratios increased for persons without opioid misuse or OUD over time.•Quit ratios did not change for those with opioid misuse or OUD over time.
The prevalence of cigarette smoking is more than two times higher among individuals with versus without opioid misuse and/or opioid use disorders (OUD). Overall, smoking cessation has increased over time although it is unknown whether it has similarly increased for those with opioid misuse or OUD. The current study examined cigarette quit ratios from 2002 to 2018 among US individuals with and without opioid misuse or OUD.
Data came from the National Survey on Drug Use and Health, a yearly cross-sectional survey of US civilians 12 years or older. Annual quit ratios (i.e., proportion of former smokers among lifetime-smokers) were estimated from 2002 to 2018. Logistic regression tested time trends in quit ratios by opioid misuse/OUD.
Past-month smoking prevalence was much higher for persons with versus without opioid misuse (64.6 % versus 25.7 %) and OUD (73.3 % versus 26.0 %). In 2018, quit ratios for individuals with opioid misuse (18.0 %) or OUD (10.0 %) were less than half of those without opioid misuse (48.3 %) or OUD (48.1 %). After adjusting for background characteristics, the quit ratio did not change over time among individuals with opioid misuse or OUD in contrast to an increase in quit ratios for those without opioid misuse or OUD. For those without opioid misuse or OUD, males had higher quit ratios than females.
Cigarette quit ratios remain dramatically lower among those with opioid misuse or OUD. Public health and clinical attention are needed to increase cessation and reduce smoking consequences for individuals with opioid misuse and OUD.
Social media is an important information source for a growing subset of the population and can likely be leveraged to provide insight into the evolving drug overdose epidemic. Twitter can provide ...valuable insight into trends, colloquial information available to potential users, and how networks and interactivity might influence what people are exposed to and how they engage in communication around drug use.
This exploratory study was designed to investigate the ways in which unsupervised machine learning analyses using natural language processing could identify coherent themes for tweets containing substance names.
This study involved harnessing data from Twitter, including large-scale collection of brand name (N=262,607) and street name (N=204,068) prescription drug-related tweets and use of unsupervised machine learning analyses (ie, natural language processing) of collected data with data visualization to identify pertinent tweet themes. Latent Dirichlet allocation (LDA) with coherence score calculations was performed to compare brand (eg, OxyContin) and street (eg, oxys) name tweets.
We found people discussed drug use differently depending on whether a brand name or street name was used. Brand name categories often contained political talking points (eg, border, crime, and political handling of ongoing drug mitigation strategies). In contrast, categories containing street names occasionally referenced drug misuse, though multiple social uses for a term (eg, Sonata) muddled topic clarity.
Content in the brand name corpus reflected discussion about the drug itself and less often reflected personal use. However, content in the street name corpus was notably more diverse and resisted simple LDA categorization. We speculate this may reflect effective use of slang terminology to clandestinely discuss drug-related activity. If so, straightforward analyses of digital drug-related communication may be more difficult than previously assumed. This work has the potential to be used for surveillance and detection of harmful drug use information. It also might be used for appropriate education and dissemination of information to persons engaged in drug use content on Twitter.
•E-cig and prior combustible use doubled the odds of cardiovascular disease (CVD).•Concurrent e-cig and combustible use elevated the odds of CVD by 2.5 times.•Exclusive e-cig use lacked a notable ...association with CVD and needs more research.
Growing evidence highlights the impact of e-cigarette use on cardiovascular health, prompting a crucial examination of its association with cardiovascular disease (CVD) in both exclusive e-cigarette and dual use scenarios with combustible cigarettes. This meta-analysis assessed the association between e-cigarette use and CVD by synthesizing the existing literature.
Pertinent observational studies were identified using multiple electronic databases, from August 22nd, 2006, to April 10th, 2024. A meta-analysis was conducted using random-effect models. Risk of bias was assessed using the National Institutes of Health (NIH) Study Quality Assessment Tools.
Findings: A total of 20 observational studies involving 8,499,444 participants were included in the meta-analysis. Dual use (e-cigarettes and combustible cigarette) increased the odds of CVD by 2.56 times (95 % CI: 2.11, 3.11) compared to never use of both. Current e-cigarette use combined with former combustible cigarette increased the odds of CVD by 2.02 times (95 % CI: 1.58, 2.58) compared to never use of either. Exclusive current e-cigarette use did not show a statistically significant association with CVD odds compared to never use of either (OR = 1.24, 95 % CI: 0.93, 1.67).
Dual use of e-cigarettes and combustible cigarettes was significantly associated with CVD, but results failed to show a significant association between exclusive e-cigarette use and CVD. Robust and longitudinal studies are needed to understand the long-term implications of e-cigarette use and CVD. Public health efforts should focus on awareness, smoking cessation, and regulating both e-cigarettes and combustible cigarettes.
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