Parent-Perceived Benefits and Harms Associated With Internet Use by Adolescent Offspring.

Importance: Limited systematic information on familial factors and perception of the benefits and harms of internet use by youths is available. Much of the current research has been hampered by small nondiverse samples and limited information on key familial and offspring characteristics. Objective: To characterize parental perceptions and concerns about internet use associated with adolescent development, well-being, safety, family connectedness, and potential for problematic internet use. Design, Setting, and Participants: A 20-minute, English-language survey was developed with expert stakeholders using previously validated questionnaires and was conducted online between June 17 and July 5, 2022. Participants included 1005 parents of children and adolescents aged 9 to 15 years drawn from an online digital survey platform and calibrated for representation with post hoc weightings. Main Outcomes and Measures: Parent survey responses about family characteristics and internet use were used to compute Internet Addiction Test scores for parents and their offspring, Alabama Parenting Questionnaire scores, and an aggregate family connectedness score. Results: The survey cohort of 1005 parents included 568 women (56.5%) and 437 men (43.5%) with a mean age (SD) of 39.5 (6.4) years. In terms of race and ethnicity, the most common categories included Black or African American (95 [9.5%]), Latinx or Hispanic (100 [10.0%]), White (602 [59.9%]), and 2 or more races or ethnicities (122 [12.1%]). Respondents endorsed parental concerns that included exposure to harmful content (646 [64.3%]) and online bullying (533 [53.0%]). Two hundred twenty-five parents (22.4%) had specific concerns about internet addiction in their adolescent offspring, and twice as many parents reported specific concerns about internet addiction than substance addiction. However, parents also indicated that internet use improved family connectedness among immediate families (468 [46.6%]) and extended families (568 [56.5%]). Internet Addiction Test scores in adolescent offspring were correlated with parent scores (ß = 0.62 [SE = 0.02]; P < .001) and Alabama Parenting Questionnaire-Inconsistent Discipline scores (ß = 0.23 [SE = 0.11]; P = .04). Conclusions and Relevance: In this survey study of parent perceptions of internet use among adolescent offspring, parents believed the internet brought families closer yet also expressed concerns. Problematic internet use among youths was correlated with negative parenting styles and parent internet use. This research adds to the literature by suggesting that families, their communities, and industry may have common ground to collaborate on reducing the negative effects of internet use.

Fell on Black Days: Analyzing the Song Lyrics of Chris Cornell for Insight into Depression and Suicide.

Chris Cornell was a guitarist, singer, songwriter, and pioneer of grunge music. Cornell struggled with mental illness and addiction and incorporated these themes into his song lyrics. At age 52, Cornell died by suicide in his hotel bathroom following a live performance. This mixed-methods study examines Cornell's song lyrics for references to negative words and themes related to depression and suicide. Two coders independently reviewed lyrical transcripts to identify the primary theme, secondary theme(s), and valence (positive or negative). Sentiment analysis, a natural language processing technique, was used to examine word frequency and valence. Songs (N = 215) were predominantly (79%) negative and contained more negative (N = 3244, 56.1%) than positive (N = 2537, 43.9%) words. Thematic analysis by stage of career shows a narrowing focus on depression, failed relationships, and morbid thoughts. Themes of depressed mood, death, and suicide were common and increased by stage of career. By applying qualitative and quantitative techniques to song lyrics, this study revealed that Cornell's songs reflect a narrative of negativity consistent with someone experiencing depression and thoughts of death and suicide. Like personal notes and poems, song lyrics may reflect symptoms of depression and suicidal thoughts warranting clinical attention.

Association between COVID-19 risk-mitigation behaviors and specific mental disorders in youth.

BACKGROUND: Although studies of adults show that pre-existing mental disorders increase risk for COVID-19 infection and severity, there is limited information about this association among youth. Mental disorders in general as well as specific types of disorders may influence the ability to comply with risk-mitigation strategies to reduce COVID-19 infection and transmission. METHODS: Youth compliance (rated as "Never," "Sometimes," "Often," or "Very often/Always") with risk mitigation was reported by parents on the CoRonavIruS Health Impact Survey (CRISIS) in January 2021. The sample comprised 314 female and 514 male participants from the large-scale Child Mind Institute Healthy Brain Network, a transdiagnostic self-referred, community sample of children and adolescents (ages 5-21). Responses were summarized using factor analysis of risk mitigation, and their associations with lifetime mental disorders (assessed via structured diagnostic interviews) were identified with linear regression analyses (adjusted for covariates). All analyses used R Project for Statistical Computing for Mac (v.4.0.5). RESULTS: A two-factor model was the best-fitting solution. Factor 1 (avoidance behaviors) included avoiding groups, indoor settings, and other peoples' homes; avoidance scores were higher among youth with any anxiety disorder (p = .01). Factor 2 (hygiene behaviors) included using hand sanitizer, washing hands, and maintaining social distance; hygiene scores were lower among youth with ADHD (combined type) (p = .02). Mask wearing was common (90%), did not load on either factor, and was not associated with any mental health disorder. CONCLUSION AND RELEVANCE: Although most mental disorders examined were not associated with risk mitigation, youth with ADHD characterized by hyperactivity plus inattention may need additional support to consistently engage in risk-mitigation behaviors. Enhancing risk-mitigation strategies among at-risk groups of youth may help reduce COVID-19 infection and transmission.

Association between COVID-19 Risk-Mitigation Behaviors and Specific Mental Disorders in Youth.

Background : Although studies of adults show that pre-existing mental disorders increase risk for COVID-19 infection and severity, there is limited information about this association among youth. Mental disorders in general as well as specific types of disorders may influence their ability to comply with risk-mitigation strategies to reduce COVID-19 infection and transmission. Methods : Youth compliance (rated as "Never," "Sometimes," "Often," or "Very often/Always") with risk mitigation was reported by parents on the CoRonavIruS Health Impact Survey (CRISIS) in January 2021. Responses were summarized using factor analysis of risk mitigation, and their associations with lifetime mental disorders (assessed via structured diagnostic interviews) were identified with linear regression analyses (adjusted for covariates). All analyses used R Project for Statistical Computing for Mac (v.4.0.5). Results : A two-factor model was the best-fitting solution. Factor 1 (avoidance behaviors) included avoiding groups, indoor settings, and other peoples' homes; avoidance was more likely among youth with any anxiety disorder (p=.01). Factor 2 (hygiene behaviors) included using hand sanitizer, washing hands, and maintaining social distance; practicing hygiene was less likely among youth with ADHD (combined type) (p=.02). Mask wearing, which did not load on either factor, was not associated with any mental health disorder. Conclusion and Relevance : Findings suggest that education and monitoring of risk-mitigation strategies in certain subgroups of youth may reduce risk of exposure to COVID-19 and other contagious diseases. Additionally, they highlight the need for greater attention to vaccine prioritization for individuals with ADHD.

Comorbidity and Coaggregation of Major Depressive Disorder and Bipolar Disorder and Cannabis Use Disorder in a Controlled Family Study.

Importance: Cannabis use disorder (CUD) is increasing in the US. Clarification of the potential mechanisms underlying the comorbidity between mood disorders and CUD may help prevent CUD. Objective: To examine co-occurrence and familial aggregation of CUD and mood disorder subtypes. Design, Setting, and Participants: In this cross-sectional, community-based study in the Washington, DC, metropolitan area, semistructured diagnostic interviews and family history reports assessed lifetime DSM-IV disorders in probands and relatives. Familial aggregation and coaggregation of CUD with mood disorders were estimated via mixed-effects models, adjusting for age, sex, recruitment source, and comorbid mood, anxiety, and other substance use disorders. A total of 586 adult probands (186 with bipolar disorder; 55 with CUD) and 698 first-degree relatives (91 with bipolar disorder; 68 with CUD) were recruited from a community screening of the greater Washington, DC, metropolitan area from May 2004 to August 2020. Inclusion criteria were ability to speak English, and availability and consent to contact at least 2 living first-degree relatives. Main Outcomes and Measures: Lifetime CUD in first-degree relatives. Results: Of 586 probands, 395 (67.4%) were female; among 698 relatives, 437 (62.6%) were female. The mean (SD) age was 47.5 (15.2) years for probands and 49.6 (18.0) years for relatives. In the proband group, 82 participants (14.0%) self-identified as African American or Black, 467 (79.7%) as White, and 37 (6.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. In the relative group, 53 participants (7.6%) self-identified as African American or Black, 594 (85.1%) as White, and 51 (7.3%) as American Indian or Alaska Native, Asian, more than one race, or another race or ethnicity or declined to respond. These groups were combined to protect privacy owing to small numbers. CUD in probands (55 [9.4%]) was associated with an increase in CUD in relatives (adjusted odds ratio [aOR], 2.64; 95% CI, 1.20-5.79; P = .02). Bipolar disorder II (BP-II) in probands (72 [12.3%]) was also associated with increased risk of CUD in relatives (aOR, 2.57; 95% CI, 1.06-6.23; P = .04). However, bipolar disorder I (114 [19.5%]) and major depressive disorder (192 [32.8%]) in probands were not significantly associated with CUD in relatives. Among relatives, CUD was associated with BP-II (aOR, 4.50; 95% CI, 1.72-11.77; P = .002), major depressive disorder (aOR, 3.64; 95% CI, 1.78-7.45; P < .001), and mean (SD) age (42.7 [12.8] years with CUD vs 50.3 [18.3] years without CUD; aOR, 0.98; 95% CI, 0.96-1.00; P = .02). Familial coaggregation of BP-II with CUD was attenuated by the inclusion of comorbid anxiety disorders. Further, rates of CUD were highest in relatives with both a familial and individual history of BP-II (no familial or individual history of BP-II: 41 [7.2%]; familial history but no individual history of BP-II: 13 [19.1%]; individual history but no familial history of BP-II: 10 [22.2%]; familial and individual history of BP-II: 4 [28.6%]; Fisher exact test, P < .001). The onset of mood disorder subtypes preceded CUD in probands and relatives in most cases. Conclusions and Relevance: The findings confirmed a familial aggregation of CUD. The increase in risk of CUD among relatives of probands with BP-II suggests that CUD may share a common underlying diathesis with BP-II. Taken together with the temporal precedence of depression and mania with respect to CUD onset, these findings highlight a potential role for BP-II intervention as CUD prevention.

Urinary Nicotine Metabolites and Self-Reported Tobacco Use Among Adults in the Population Assessment of Tobacco and Health (PATH) Study, 2013-2014.

INTRODUCTION: The Population Assessment of Tobacco and Health (PATH) Study is a longitudinal cohort study on tobacco use behavior, attitudes and beliefs, and tobacco-related health outcomes, including biomarkers of tobacco exposure in the U.S. population. In this report we provide a summary of urinary nicotine metabolite measurements among adult users and non-users of tobacco from Wave 1 (2013-2014) of the PATH Study. METHODS: Total nicotine and its metabolites including cotinine, trans-3'-hydroxycotinine (HCTT), and other minor metabolites were measured in more than 11 500 adult participants by liquid chromatography tandem mass spectrometry methods. Weighted geometric means (GM) and least square means from statistical modeling were calculated for non-users and users of various tobacco products. RESULTS: Among daily users, the highest GM concentrations of nicotine, cotinine and HCTT were found in exclusive smokeless tobacco users, and the lowest in exclusive e-cigarette users. Exclusive combustible product users had intermediate concentrations, similar to those found in users of multiple products (polyusers). Concentrations increased with age within the categories of tobacco users, and differences associated with gender, race/ethnicity and educational attainment were also noted among user categories. Recent (past 12 months) former users had GM cotinine concentrations that were more than threefold greater than never users. CONCLUSIONS: These urinary nicotine metabolite data provide quantification of nicotine exposure representative of the entire US adult population during 2013-2014 and may serve as a reference for similar analyses in future measurements within this study. IMPLICATIONS: Nicotine and its metabolites in urine provide perhaps the most fundamental biomarkers of recent nicotine exposure. This report, based on Wave 1 of the Population Assessment of Tobacco and Health (PATH) Study, provides the first nationally representative data describing urinary nicotine biomarker concentrations in both non-users, and users of a variety of tobacco products including combustible, e-cigarette and smokeless products. These data provide a urinary biomarker concentration snapshot in time for the entire US population during 2013-2014, and will provide a basis for comparison with future results from continuing, periodic evaluations in the PATH Study.

Association between COVID-19 Risk-Mitigation Behaviors and Specific Mental Disorders in Youth.

Importance: Although studies of adults show that pre-existing mental disorders increase risk for COVID-19 infection and severity, there is limited information about this association among youth. Mental disorders in general as well as specific types of disorders may influence their ability to comply with risk-mitigation strategies to reduce COVID-19 infection and transmission. Objective: To examine associations between specific mental disorders and COVID-19 risk-mitigation practices among 314 female and 514 male youth. Design: Youth compliance (rated as "Never," "Sometimes," "Often," or "Very often/Always") with risk mitigation was reported by parents on the CoRonavIruS Health Impact Survey (CRISIS) in January 2021. Responses were summarized using factor analysis of risk mitigation, and their associations with lifetime mental disorders (assessed via structured diagnostic interviews) were identified with linear regression analyses (adjusted for covariates). All analyses used R Project for Statistical Computing for Mac (v.4.0.5). Setting: The Healthy Brain Network (HBN) in New York City Participants. 314 female and 514 male youth (ages 5-21). Main Outcomes and Measures: COVID-19 risk mitigation behaviors among youth. Results: A two-factor model was the best-fitting solution. Factor 1 (avoidance behaviors) included avoiding groups, indoor settings, and other peoples' homes; avoidance was more likely among youth with any anxiety disorder (p=.01). Factor 2 (hygiene behaviors) included using hand sanitizer, washing hands, and maintaining social distance; practicing hygiene was less likely among youth with ADHD (combined type) (p=.02). Mask wearing, which did not load on either factor, was not associated with any mental health disorder. Conclusion and Relevance: Findings suggest that education and monitoring of risk-mitigation strategies in certain subgroups of youth may reduce risk of exposure to COVID-19 and other contagious diseases. Additionally, they highlight the need for greater attention to vaccine prioritization for individuals with ADHD. Key Points: Question: Are mental disorders among youth associated with COVID-19 risk-mitigation behaviors?Findings: Based on the parent CoRonavIruS Health Impact Survey (CRISIS) of 314 females and 514 males aged 5-21, youth with anxiety disorders were more likely to avoid high-risk exposure settings, and those with ADHD (combined type) were less likely to follow hygiene practices. In contrast, mask wearing was not associated with youth mental disorders.Meaning: Specific types of disorders in youth may interfere with their ability to employ risk-mitigation strategies that may lead to greater susceptibility to COVID-19.

Rural and urban differences in undersupply of buprenorphine provider availability in the United States, 2018.

BACKGROUND: Medications to treat opioid use disorder (OUD) including buprenorphine products are evidence-based and cost-effective tools for combating the opioid crisis. However, limited availability to buprenorphine is pervasive in the United States (US) and may serve to exacerbate the deadly epidemic. Although prior research points to rural counties as especially needy of strategies that improve buprenorphine availability, it is important to investigate the availability of waivered providers according to treatment need as defined by the county-level rate of opioid-overdose deaths (OOD). This study examined differences in buprenorphine provider availability relative to treatment need among rural and urban counties in the US. METHODS: Buprenorphine provider availability relative to need in each county was defined as the number of waivered providers divided by the rate of OODs (i.e., number of OODs/100,000 population), according to 2018 data. Counties with ratios in the bottom tertile of their state were classified as buprenorphine undersupplied. We estimated logit models to statistically test the association of rurality and state main effects and their interaction terms (independent variables) and the county classified as buprenorphine undersupplied (dependent variable). RESULTS: A total of 38 states and 2595 counties had sufficient non-suppressed data to remain in the analysis. A larger percent of urban counties (36.43%) than rural counties (32.01%) were classified as buprenorphine undersupplied (p = 0.001). The likelihood of a rural county being undersupplied varied considerably by state (Chi Square = 82.88, p = 0.000). All states with significant (p < 0.05 or p < 0.10) interaction terms showed lower likelihood of buprenorphine undersupply in rural counties. CONCLUSIONS: The rural-urban distribution in undersupply of waivered buprenorphine providers relative to need varied markedly by state. Strategies for improving access to buprenorphine-waivered providers should be state-centric and informed by county-specific indicators of need.

Mood and anxiety profiles differentially associate with physical conditions in US adolescents.

BACKGROUND: Mood and anxiety are widely associated with physical conditions, but research and treatment are complicated by their overlap, clinical heterogeneity, and manifestation on a spectrum rather than as discrete disorders. In contrast to previous work relying on threshold-level disorders, we examined the association between empirically-derived profiles of mood and anxiety syndromes with physical conditions in a nationally-representative sample of US adolescents. METHODS: Participants were 2,911 adolescents (aged 13-18) from the National Comorbidity Survey-Adolescent Supplement who provided information on physical conditions and reported at least one lifetime mood-anxiety 'syndrome' based on direct interviews with the Composite International Diagnostic Interview Version 3.0. Mood-anxiety syndromes reflected 3-level ratings from subthreshold to severe distress/impairment, and subtyped mood episodes. Stepwise latent profile analysis identified mood-anxiety profiles and tested associations with physical conditions. RESULTS: Three mood-anxiety profiles were identified: "Mood-GAD" (25.6%)-non-atypical depression, mania, generalized anxiety; "Atypical-Panic" (11.3%)-atypical depression, panic; and "Reference" (63.1%)-lower mood and anxiety except specific phobia. Headaches were more prevalent in Mood-GAD and Atypical-Panic than Reference (47.9%, 50.1%, and 37.7%, respectively; p=0.011). Heart problems were more common in Mood-GAD than Atypical-Panic (7.4% v 2.2%, p=0.004) and Reference, with back/neck pain more prevalent in Mood-GAD than Reference (22.5% v 15.3%, p=0.016). LIMITATIONS: Broad categories of physical conditions without information on specific diagnoses; replication regarding specificity is recommended. CONCLUSIONS: Heart problems and pain-related conditions were differentially associated with specific mood-anxiety profiles. Subtyping depression and anxiety-inclusive of subthreshold syndromes-and their patterns of clustering may facilitate etiologic and intervention work in multimorbidity.

Validation of the Wave 1 and Wave 2 Population Assessment of Tobacco and Health (PATH) Study Indicators of Tobacco Dependence Using Biomarkers of Nicotine Exposure Across Tobacco Products.

INTRODUCTION: This study examined the predictive relationships between biomarkers of nicotine exposure and 16-item self-reported level of tobacco dependence (TD) and subsequent tobacco use outcomes. AIMS AND METHODS: The Population Assessment of Tobacco and Health (PATH) Study surveyed adult current established tobacco users who provided urine biospecimens at Wave 1 (September 2013-December 2014) and completed the Wave 2 (October 2014-October 2015) interview (n = 6872). Mutually exclusive user groups at Wave 1 included: Cigarette Only, E-cigarette Only, Cigar Only, Hookah Only, Smokeless Tobacco Only, Cigarette Plus E-cigarette, multiple tobacco product users who smoked cigarettes, and multiple tobacco product users who did not smoke cigarettes. Total Nicotine Equivalents (TNE-2) and TD were measured at Wave 1. Approximate one-year outcomes included frequency/quantity used, quitting, and adding/switching to different tobacco products. RESULTS: For Cigarette Only smokers and multiple tobacco product users who smoked cigarettes, higher TD and TNE-2 were associated with: a tendency to smoke more, smoking more frequently over time, decreased likelihood of switching away from cigarettes, and decreased probability of quitting after one year. For other product user groups, Wave 1 TD and/or TNE-2 were less consistently related to changes in quantity and frequency of product use, or for adding or switching products, but higher TNE-2 was more consistently predictive of decreased probability of quitting. CONCLUSIONS: Self-reported TD and nicotine exposure assess common and independent aspects of dependence in relation to tobacco use behaviors for cigarette smokers. For other product user groups, nicotine exposure is a more consistent predictor of quitting than self-reported TD. IMPLICATIONS: This study suggests that smoking cigarettes leads to the most coherent pattern of associations consistent with a syndrome of TD. Because cigarettes continue to be prevalent and harmful, efforts to decrease their use may be accelerated via conventional means (eg, smoking cessation interventions and treatments), but also perhaps by decreasing their dependence potential. The implications for noncombustible tobacco products are less clear as the stability of tobacco use patterns that include products such as e-cigarettes continue to evolve. TD, nicotine exposure measures, and consumption could be used in studies that attempt to understand and predict product-specific tobacco use behavioral outcomes.

Serum Concentrations of Cotinine and Trans-3'-Hydroxycotinine in US Adults: Results From Wave 1 (2013-2014) of the Population Assessment of Tobacco and Health Study.

INTRODUCTION: The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative cohort of tobacco product users and nonusers. The study's main purpose is to obtain longitudinal epidemiologic data on tobacco use and exposure among the US population. AIMS AND METHODS: Nicotine biomarkers-cotinine (COT) and trans-3'-hydroxycotinine (HCT)-were measured in blood samples collected from adult daily tobacco users and nonusers during Wave 1 of the PATH Study (2013-2014; n = 5012; one sample per participant). Participants' tobacco product use and exposure to secondhand smoke were categorized based on questionnaire responses. Nonusers were subdivided into never users and recent former users. Daily tobacco users were classified into seven tobacco product use categories: exclusive users of cigarette, smokeless tobacco, electronic cigarette, cigar, pipe, and hookah, as well as polyusers. We calculated sample-weighted geometric mean (GM) concentrations of cotinine, HCT, and the nicotine metabolite ratio (NMR) and evaluated their associations with tobacco use with adjustment for potential confounders. RESULTS: The GMs (95% confidence intervals) of COT and HCT concentrations for daily tobacco users were 196 (184 to 208) and 72.5 (67.8 to 77.4) ng/mL, and for nonusers they were 0.033 (0.028 to 0.037) and 0.021 (0.018 to 0.023) ng/mL. Exclusive smokeless tobacco users had the highest COT concentrations of all user groups examined. The GM NMR in daily users was 0.339 (95% confidence interval: 0.330 to 0.350). CONCLUSIONS: These nationally representative estimates of serum nicotine biomarkers could be the basis for reference ranges characterizing nicotine exposure for daily tobacco users and nonusers in the US adult population. IMPLICATIONS: This report summarizes the serum nicotine biomarker measurements in Wave 1 of the PATH Study. We are reporting the first estimates of HCT in serum for daily tobacco users and nonusers in the noninstitutionalized, civilian US adult population; the first nationally representative serum COT estimates for daily exclusive users of different tobacco products and daily polyusers; and the first nationally representative estimate of the serum NMR in daily tobacco users by age, race/ethnicity, and sex.

Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study.

BACKGROUND: The Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12. METHODS: This study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD). PRIMARY RESULTS: At baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine, <0.1 % used any other drug of abuse). Analyses revealed that total caffeine use and early alcohol sipping were associated with demographic variables (p's<.05), externalizing symptoms (caffeine p = 0002; sipping p = .0003), and parental history of AUD (sipping p = .03). CONCLUSIONS: ABCD Study participants aged 9-10 years old reported caffeine use and alcohol sipping experimentation, but very rare other SU. Variables linked with early childhood alcohol sipping and caffeine use should be examined as contributing factors in future longitudinal analyses examining escalating trajectories of SU in the ABCD Study cohort.

Predictive validity of the adult tobacco dependence index: Findings from waves 1 and 2 of the Population Assessment of Tobacco and Health (PATH) study.

BACKGROUND AND AIMS: Building on published work1 establishing concurrent validity of a self-report tobacco dependence (TD) index among users of different tobacco products in Wave 1 (W1) of the Population Assessment of Tobacco and Health (PATH) Study, the current study examines prospective relationships with tobacco use behaviors to establish predictive validity of the TD index. Hypotheses suggested high levels of W1 TD would be associated with persistent tobacco use at Wave 2 (W2). PARTICIPANTS: A U.S. nationally representative sample of 32,320 adult W1 and W2 interviews focused on 11,615 W1 adults who were current established tobacco users and completed the W2 interview. FINDINGS: Higher TD scores and greater changes in TD scores were associated with greater quantity and frequency of tobacco use at the W2 interview for Cigarette Only (n = 7068), Smokeless (smokeless or snus pouches) Only (n = 772), Cigarette plus E-Cigarette (n = 592), and Multiple Products (n = 1866) users, although not significantly so for E-Cigarette Only (n = 367), Cigar Only (traditional, cigarillo, or filtered) (n = 584), or Hookah Only (n = 366) users. Higher TD was associated with decreased odds of successful quitting for Cigarette and Multiple Product users. Higher TD was associated with increased odds of a quit attempt for those in the Hookah and Multiple Products user groups and was not associated with quit attempts or deceased odds of quit success among exclusive E-Cigarette, Cigar, Smokeless and Cigarette plus E-Cigarette users. CONCLUSION: Support for the predictive validity of the PATH Study measures of adult TD will enable regulatory investigations of TD across several tobacco products.

Using Twitter to Surveil the Opioid Epidemic in North Carolina: An Exploratory Study.

BACKGROUND: Over the last two decades, deaths associated with opioids have escalated in number and geographic spread, impacting more and more individuals, families, and communities. Reflecting on the shifting nature of the opioid overdose crisis, Dasgupta, Beletsky, and Ciccarone offer a triphasic framework to explain that opioid overdose deaths (OODs) shifted from prescription opioids for pain (beginning in 2000), to heroin (2010 to 2015), and then to synthetic opioids (beginning in 2013). Given the rapidly shifting nature of OODs, timelier surveillance data are critical to inform strategies that combat the opioid crisis. Using easily accessible and near real-time social media data to improve public health surveillance efforts related to the opioid crisis is a promising area of research. OBJECTIVE: This study explored the potential of using Twitter data to monitor the opioid epidemic. Specifically, this study investigated the extent to which the content of opioid-related tweets corresponds with the triphasic nature of the opioid crisis and correlates with OODs in North Carolina between 2009 and 2017. METHODS: Opioid-related Twitter posts were obtained using Crimson Hexagon, and were classified as relating to prescription opioids, heroin, and synthetic opioids using natural language processing. This process resulted in a corpus of 100,777 posts consisting of tweets, retweets, mentions, and replies. Using a random sample of 10,000 posts from the corpus, we identified opioid-related terms by analyzing word frequency for each year. OODs were obtained from the Multiple Cause of Death database from the Centers for Disease Control and Prevention Wide-ranging Online Data for Epidemiologic Research (CDC WONDER). Least squares regression and Granger tests compared patterns of opioid-related posts with OODs. RESULTS: The pattern of tweets related to prescription opioids, heroin, and synthetic opioids resembled the triphasic nature of OODs. For prescription opioids, tweet counts and OODs were statistically unrelated. Tweets mentioning heroin and synthetic opioids were significantly associated with heroin OODs and synthetic OODs in the same year (P=.01 and P<.001, respectively), as well as in the following year (P=.03 and P=.01, respectively). Moreover, heroin tweets in a given year predicted heroin deaths better than lagged heroin OODs alone (P=.03). CONCLUSIONS: Findings support using Twitter data as a timely indicator of opioid overdose mortality, especially for heroin.

Longitudinal associations between susceptibility to tobacco use and the onset of other substances among U.S. youth.

We examined whether tobacco susceptibility at Wave (W) 1 (2013-2014) predicts the onset of tobacco and other substances at W2 (2014-2015) among 5325 U.S. youth (12-17 years) never substance users at W1 in the Population Assessment of Tobacco and Health (PATH) Study. Tobacco susceptibility was based on curiosity, use intentions, and response to a best friend's offer to use. Onset of use included past 12-month use of a specific substance or group of substances at W2 among those who had never used any substance at W1. Approximately, 31.3% of W1 youth were susceptible to tobacco use. W2 onset was 8.2% (SE = 0.4) for alcohol exclusively, 5.0% (SE = 0.4) for polysubstance including tobacco, 4.4% (SE = 0.3) for tobacco exclusively, 3.1% (SE = 0.3) for other drugs (misused prescription stimulants and painkillers, cocaine, other stimulants, heroin, inhalants, solvents and hallucinogens) exclusively, 1.4% (SE = 0.2) for polysubstance excluding tobacco, and 0.9% (SE = 0.1) for marijuana exclusively. Tobacco-susceptible compared with non-tobacco susceptible youth had higher odds of onset of exclusive tobacco use (AOR: 2.4; 95% CI: 1.7, 3.3), exclusive alcohol use (AOR: 1.5; 95% CI: 1.2, 1.8), and polysubstance use (AOR: 3.9; 95% CI: 2.8, 5.6 including tobacco and AOR: 1.8; 95% CI: 1.1, 3.0 excluding tobacco) compared with W2 never substance use. In this national study, tobacco susceptibility identified U.S. youth at risk for onset of tobacco and other substances, perhaps reflecting common etiology and clustering of substance use in youth. Identifying and preventing tobacco-susceptible youth from progressing to using addictive substances must remain a public health priority.

Association of Flavored Tobacco Use With Tobacco Initiation and Subsequent Use Among US Youth and Adults, 2013-2015.

Importance: Flavors in tobacco products may appeal to young and inexperienced users. Objective: To examine among youth (aged 12-17 years), young adults (aged 18-24 years), and adults (aged ≥25 years) the prevalence of first use of flavored tobacco products among new tobacco users and the association between first flavored use of a given tobacco product and tobacco use 1 year later, including progression of tobacco use. Design, Setting, and Participants: This cohort study represents a longitudinal analysis of data from the Population Assessment of Tobacco and Health (PATH) Study, a nationally representative study with data collected in 2013 to 2014 (wave 1) and 2014 to 2015 (wave 2). Participants were noninstitutionalized individuals, including 11 996 youth and 26 447 adults, in selected households who participated in both waves of the PATH Study. Data analysis was conducted from July 2016 to June 2019. Main Outcomes and Measures: Prevalence of tobacco product use at wave 2. Results: The mean (SE) age of the participants was 14.5 (0.0) years for youth, 21.1 (0.0) years for young adults, and 50.3 (0.0) for adults. Most youth (71.9%; 95% CI, 69.7%-74.0%) and young adults (57.6%; 95% CI, 54.9%-60.3%) who were new users of tobacco products over the 10- to 13-month follow-up period used flavored products. First use of a menthol or mint or other flavored cigarette documented at wave 1 was positively associated with past 12-month and past 30-day cigarette use in all age groups at wave 2 compared with first use of a nonflavored cigarette (youth, flavored cigarette, past 12-month use adjusted prevalence ratio [aPR], 1.14 [95% CI, 1.05-1.25] and past 30-day use aPR, 1.15 [95% CI, 1.00-1.31]; youth, menthol or mint cigarette, past 12-month use aPR, 1.18 [95% CI, 1.08-1.29] and past 30-day use aPR, 1.19 [95% CI, 1.04-1.37]; young adult, flavored cigarette, past 12-month use aPR, 1.09 [95% CI, 1.04-1.15] and past 30-day use aPR, 1.13 [95% CI, 1.06-1.21]; young adult menthol or mint cigarette, past 12-month use aPR, 1.10 [95% CI, 1.05-1.16] and past 30-day use aPR, 1.15 [95% CI, 1.07-1.23]; adult flavored cigarette, past 12-month use aPR, 1.10 [95% CI, 1.05-1.15] and past 30-day use aPR, 1.09 [95% CI, 1.04-1.14]; adult menthol or mint cigarette, past 12-month use aPR, 1.13 [95% CI, 1.08-1.18] and past 30-day use aPR, 1.12 [95% CI, 1.07-1.17]). Among young adults, first use of flavored e-cigarettes (aPR, 2.05; 95% CI, 1.61-2.61), any cigars (aPR, 1.60; 95% CI, 1.26-2.02), cigarillos (aPR, 1.49; 95% CI, 1.08-2.05), filtered cigars (aPR, 3.69; 95% CI, 2.08-6.57), hookah (aPR, 1.91; 95% CI, 1.23-2.98), and any smokeless tobacco (aPR, 1.54; 95% CI, 1.08-2.20) was prospectively associated with current regular use of those products at wave 2 compared with first nonflavored use. Among adults aged 25 years and older, first use of flavored e-cigarettes (aPR, 1.60; 95% CI, 1.41-1.82), any cigars (aPR, 1.56; 95% CI, 1.29-1.87), cigarillos (aPR, 1.29; 95% CI, 1.01-1.64), filtered cigars (aPR, 1.79; 95% CI, 1.25-2.54), hookah (aPR, 5.66; 95% CI, 2.04-15.71), and any smokeless tobacco (aPR, 1.55; 95% CI, 1.32-1.82) was prospectively associated with current regular use of those products at wave 2 compared with first nonflavored use. Conclusions and Relevance: In this longitudinal cohort study, flavors in tobacco products were associated with youth and young adult tobacco experimentation. First use of a flavored tobacco product may place youth, young adults, and adults at risk of subsequent tobacco use.

Patterns and correlates of polysubstance use among US youth aged 15-17 years: wave 1 of the Population Assessment of Tobacco and Health (PATH) Study.

BACKGROUND AND AIMS: Youth aged 15-17 years are at high risk of tobacco, alcohol and drug use. Given the changing landscape with respect to availability, use of emerging products and regulatory environments, we examined patterns and correlates of polysubstance use among US youth aged 15-17 years. DESIGN: Cross-sectional self-reported data. SETTING: United States. PARTICIPANTS: A total of 6127 US youth aged 15-17 years from wave 1 (2013-14) of the nationally representative Population Assessment of Tobacco and Health (PATH) Study. MEASUREMENTS: Latent class analysis was used to identify subgroups of polysubstance use, including 12 tobacco products, alcohol, marijuana, prescription drugs and other drugs. Socio-demographic characteristics, residence in urban area, sensation-seeking, sexual orientation and internalizing and externalizing problems were examined as correlates. FINDINGS: Approximately 43.5% of 15-17-year-olds had used at least one substance in the past 12 months. A 5-class model was identified: class 1 'abstainers' (67.3%), class 2 'alcohol users' (19.2%), class 3 'alcohol, marijuana and tobacco (AMTpredominant AM ) users' (8.2%), class 4 'alcohol, marijuana and tobacco (AMTpredominant T ) users' (3.9%) and class 5 'alcohol, marijuana, tobacco and other drug (AMTOD) users' (1.4%). Abstainers were considered the reference class. Higher sensation-seeking scores, higher age and lower academic grades were each associated with greater likelihood of membership in all user classes. Gender, race/ethnicity, parents/guardians' education, residence in non-urban areas and sexual minority groups were associated with membership in some, but not all, user classes. Compared with no/low/moderate severity, high severity internalizing problems were associated with membership in classes 2, 3 and 5, whereas high severity externalizing problems were associated with membership in classes 3 and 5 only. CONCLUSIONS: There appear to be three heterogeneous polysubstance use classes among US youth aged 15-17 years. Correlates of substance use among US youth include higher sensation-seeking, poor academic performance, non-urban residence, minority sexual orientation and mental health problems.

Urinary concentrations of monohydroxylated polycyclic aromatic hydrocarbons in adults from the U.S. Population Assessment of Tobacco and Health (PATH) Study Wave 1 (2013-2014).

BACKGROUND: Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants formed from incomplete combustion of organic matter; some PAHs are carcinogens. Smoking, diet, and other activities contribute to exposure to PAHs. Exposure data to PAHs among combustible tobacco product users (e.g. cigarette smokers) exist; however, among non-combustible tobacco products users (e.g., e-cigarette users), such data are rather limited. OBJECTIVES: We sought to evaluate exposure to PAHs among participants in Wave 1 (2013-2014) of the Population Assessment of Tobacco and Health (PATH) Study based on the type of tobacco product (combustible vs non-combustible), and frequency and intensity of product use. METHODS: We quantified seven PAH urinary biomarkers in 11,519 PATH Study participants. From self-reported information, we categorized 8327 participants based on their use of tobacco products as never-tobacco user (never user, n = 1700), exclusive current established combustible products user (combustible products user, n = 5767), and exclusive current established non-combustible products user (non-combustible products user, n = 860). We further classified tobacco users as exclusive cigarette user (cigarette user, n = 3964), exclusive smokeless product user (SLT user, n = 509), and exclusive e-cigarette user (e-cigarette user, n = 280). Last, we categorized frequency of product use (everyday vs some days) and time since use (last hour, within 3 days, over 3 days). We calculated geometric mean (GM) concentrations, and evaluated associations between tobacco product user categories and PAH biomarkers concentrations. RESULTS: Combustible products users had significantly higher GMs of all biomarkers than non-combustible products users and never users; non-combustible products users had significantly higher GMs than never users for four of seven biomarkers. For all biomarkers examined, cigarette users had the highest GMs compared to other tobacco-product users. Interestingly, GMs of 2-hydroxyfluorene, 3-hydroxyfluorene and ∑2,3-hydroxyphenanthrene were significantly higher in SLT users than in e-cigarette users; 3-hydroxyfluorene and 1-hydroxypyrene were also significantly higher in e-cigarette and SLT users than in never users. Everyday cigarette and SLT users had significantly higher GMs for most biomarkers than some days' users; cigarette and SLT users who used the product in the last hour had significantly higher GMs of most biomarkers than other occasional cigarette or SLT users respectively. By contrast, everyday e-cigarette users' GMs of most biomarkers did not differ significantly from those in some days' e-cigarette users; we did not observe clear trends by time of last use among e-cigarette users. CONCLUSIONS: Users of tobacco products had higher PAH urinary biomarker concentrations compared to never users, and concentrations differed by type and frequency of tobacco product use.

Mental Health Problems and Onset of Tobacco Use Among 12- to 24-Year-Olds in the PATH Study.

OBJECTIVE: To examine whether mental health problems predict incident use of 12 different tobacco products in a nationally representative sample of youth and young adults. METHOD: This study analyzed Wave (W) 1 and W2 data from 10,533 12- to 24-year-old W1 never tobacco users in the Population Assessment of Tobacco and Health (PATH) Study. Self-reported lifetime internalizing and externalizing symptoms were assessed at W1. Past 12-month use of cigarettes, electronic nicotine delivery systems (ENDS), traditional cigars, cigarillos, filtered cigars, pipe, hookah, snus pouches, other smokeless tobacco, bidis and kreteks (youth only), and dissolvable tobacco was assessed at W2. RESULTS: In multivariable regression analyses, high-severity W1 internalizing (adjusted odds ratio [AOR] = 1.5, 95% CI = 1.3-1.8) and externalizing (AOR = 1.3, 95% CI = 1.1-1.5) problems predicted W2 onset of any tobacco use compared to no/low/moderate severity. High-severity W1 internalizing problems predicted W2 use onset across most tobacco products. High-severity W1 externalizing problems predicted onset of any tobacco (AOR = 1.6, 95% CI = 1.3-1.8), cigarettes (AOR = 1.4, 95% CI = 1.0-2.0), ENDS (AOR = 1.8, 95% CI = 1.5-2.1), and cigarillos (AOR = 1.5, 95% CI = 1.0-2.1) among youth only. CONCLUSION: Internalizing and externalizing problems predicted onset of any tobacco use. However, findings differed for internalizing and externalizing problems across tobacco products, and by age, gender, and race/ethnicity. In addition to screening for tobacco product use, health care providers should screen for a range of mental health problems as a predictor of tobacco use. Interventions addressing mental health problems may prevent youth from initiating tobacco use.