Statistical methods for predicting e-cigarette use events based on beat-to-beat interval (BBI) data collected from wearable devices.

The prevalence of e-cigarette use among young adults in the USA is high (14%). Although the majority of users plan to quit vaping, the motivation to make a quit attempt is low and available support during a quit attempt is limited. Using wearable sensors to collect physiological data (eg, heart rate) holds promise for capturing the right timing to deliver intervention messages. This study aims to fill the current knowledge gap by proposing statistical methods to (1) de-noise beat-to-beat interval (BBI) data from smartwatches worn by 12 young adult regular e-cigarette users for 7 days; and (2) summarize the de-noised data by event and control segments. We also conducted a comprehensive review of conventional methods for summarizing heart rate variability (HRV) and compared their performance with the proposed method. The results show that the proposed singular spectrum analysis (SSA) can effectively de-noise the highly variable BBI data, as well as quantify the proportion of total variation extracted. Compared to existing HRV methods, the proposed second order polynomial model yields the highest area under the curve (AUC) value of 0.76 and offers better interpretability. The findings also indicate that the average heart rate before vaping is higher and there is an increasing trend in the heart rate before the vaping event. Importantly, the development of increasing heart rate observed in this study implies that there may be time to intervene as this physiological signal emerges. This finding, if replicated in a larger scale study, may inform optimal timings for delivering messages in future intervention.

Efficient matrix profile computation with Euclidean distance using Eigen transformation: Performance evaluation based on beat-to-beat interval (BBI) data.

The matrix profile serves as a fundamental tool to provide insights into similar patterns within time series. Existing matrix profile algorithms have been primarily developed for the normalized Euclidean distance, which may not be a proper distance measure in many settings. The methodology work of this paper was motivated by statistical analysis of beat-to-beat interval (BBI) data collected from smartwatches to monitor e-cigarette users' heart rate change patterns for which the original Euclidean distance ( L 2 $$ {L}_2 $$ -norm) would be a more suitable choice. Yet, incorporating the Euclidean distance into existing matrix profile algorithms turned out to be computationally challenging, especially when the time series is long with extended query sequences. We propose a novel methodology to efficiently compute matrix profile for long time series data based on the Euclidean distance. This methodology involves four key steps including (1) projection of the time series onto eigenspace; (2) enhancing singular value decomposition (SVD) computation; (3) early abandon strategy; and (4) determining lower bounds based on the first left singular vector. Simulation studies based on BBI data from the motivating example have demonstrated remarkable reductions in computational time, ranging from one-fourth to one-twentieth of the time required by the conventional method. Unlike the conventional method of which the performance deteriorates sharply as the time series length or the query sequence length increases, the proposed method consistently performs well across a wide range of the time series length or the query sequence length.

E-cigarette use reasons and associated e-cigarette use dependence among college students: A longitudinal examination.

OBJECTIVE: Previous studies have established an understanding of reasons for e-cigarette use and associated e-cigarette use patterns such as use frequency, yet the critical extension to associated e-cigarette dependence outcome remains under-researched. This study used longitudinal data to examine whether the reasons for e-cigarette use predict a higher/lower level of e-cigarette dependence. METHODS: This study recruited college students who were current e-cigarette users from Fall 2019 to Fall 2020 (four semesters) at three public universities in the Midwest and South of the U.S. Those who participated for at least two semesters were included (N = 366). Data were collected using a structured questionnaire. E-cigarette use dependence was assessed using the Penn State Electronic Cigarette Dependence Index. A linear mixed model with a random intercept and a random slope was conducted to examine the longitudinal association between reasons for e-cigarette use and dependence, controlling for demographics and other covariates. RESULTS: Participants who used e-cigarettes for relaxation (ß = 0.63, p < 0.05) and due to their good taste (ß = 0.63, p < 0.05) had a higher level of e-cigarette dependence. Participants using e-cigarettes for experimental purposes had a lower level of e-cigarette dependence (ß = -1.21, p < 0.01). CONCLUSIONS: These findings highlight the importance of addressing e-cigarette use reasons and their relationship to e-cigarette dependence. Prevention and intervention efforts aimed at developing more effective strategies should consider the various e-cigarette use reasons associated with dependence risks, such as enhancing awareness of the use dependence risk related to good taste of e-cigarettes and use for relaxation, as well as incorporating early screenings for use.

Estimation of Health Risks Caused by Metals Contained in E-Cigarette Aerosol through Passive Vaping.

It is expected that secondary exposure to e-cigarette aerosol (passive vaping) will soon become an issue of public health. Passive vaping inhales e-cigarette aerosol containing similar harmful substances as active vaping. However, parallel studies on passive vaping are minimal. Therefore, there is a need for passive vaping-related health risk studies to assess the impact of vaping on public health. This research conducted a series of experiments in a room using a puffing machine and the Mobile Aerosol Lung Deposition Apparatus (MALDA) to study e-cigarette aerosol respiratory deposition through passive vaping. The experimental data acquired were applied to estimate the deposited mass and health risks caused by toxic metals contained in e-cigarette aerosol. Five popular e-cigarette products were used in this study to generate e-cigarette aerosol for deposition experiments. In addition, size-segregated e-cigarette aerosol samples were collected, and metal compositions in the e-cigarette aerosol were analyzed. Results obtained showed that estimated non-cancer risks were all acceptable, with hazard quotient and hazard index all less than 1.0. The calculated cancer risks were also found acceptable, with lifetime excess cancer risk generally less than 1E-6. Therefore, the e-cigarettes tested and the passive vaping exposure scenarios studied do not seem to induce any potential for metal-related respiratory health effects.

Dependence motives and use contexts that predicted smoking cessation and vaping cessation: A two-year longitudinal study with 13 waves.

INTRODUCTION: Prior studies examining the impact of e-cigarette use, dependence, cessation motivation/goals, and environmental restriction on smoking cessation were based on cross-sectional or shorter-term longitudinal data with binary outcomes. There is also a critical knowledge gap in corresponding impact on vaping cessation. This study aims to fill in these gaps by investigating these factors' effects on speed of progression to smoking and vaping cessation. METHODS: This study conducted secondary analysis of data from 13 waves of assessment of adult cigarette users in Wisconsin from October 2015 through July 2019. Cox regression was employed to examine baseline predictors' effects on speed of progression to smoking cessation (past-month abstinence) among 405 exclusive combustible cigarette users and dual users of combustible and electronic cigarettes, as well as progression to vaping cession among 178 dual users. RESULTS: Dual use of e-cigarettes with cigarettes, lower primary dependence motives of smoking, higher secondary dependence motives of smoking, higher motivation to quit smoking, more ambitious future goals to quit smoking, and more restrictive environment for smoking all contributed to quicker progression to smoking cessation. Dual users with higher secondary dependence motives of smoking or with lower primary dependence motives of vaping progressed faster to vaping cessation. CONCLUSIONS: The findings support that nicotine dependence is product-specific with two distinct constructs: the primary dependence motives are associated with more difficulty to quit, whereas the secondary dependence motives have the opposite effect. Dual users with strong instrumental reasons for smoking may not find e-cigarettes as an effective substitute for cigarettes.

Retrospective and Real-time Measures of the Quantity of E-cigarette Use: An Ecological Momentary Assessment Study.

INTRODUCTION: Quantifying e-cigarette use is challenging because of the wide variety of products and the lack of a clear, objective demarcation of a use event. This study aimed to characterize the difference between retrospective and real-time measures of the quantity of e-cigarette use and identify the covariates that may account for discrepancies between the two types of measures. METHODS: This study analyzed data from 401 college student e-cigarette users in Indiana and Texas who responded to a web survey (retrospective) and 7-day ecological momentary assessments (EMA) (real-time) on their e-cigarette use behavior, dependence symptomatology, e-cigarette product characteristics, and use contexts from Fall 2019 to Fall 2021. Generalized linear mixed models were used to model the real-time measures of quantity offset by the retrospective average quantity. RESULTS: Although the number of times using e-cigarettes per day seems to be applicable to both retrospective and real-time measures, the number reported via EMA was 8.5 times the retrospective report. E-cigarette users with higher e-cigarette primary dependence motives tended to report more daily nicotine consumption via EMA than their retrospective reports (ie, perceived average consumption). Other covariates that were associated with discrepancies between real-time and retrospective reports included gender, nicotine concentration, using a menthol- or fruit-flavored product, co-use with alcohol, and being with others when vaping. CONCLUSIONS: The study found extreme under-reporting of e-cigarette consumption on retrospective surveys. Important covariates identified to be associated with higher than average consumption may be considered as potential targets for future vaping interventions. IMPLICATIONS: This is the first study that characterizes the direction and magnitude of the difference between retrospective and real-time measures of the quantity of e-cigarette use among young adults-the population most likely to use e-cigarettes. An average retrospective account of vaping events per day may significantly underestimate e-cigarette use frequency among young adults. The lack of insight into the degree of consumption among users with heavy primary dependence motives illustrates the importance of incorporating self-monitoring into cessation interventions.

An Exploratory Study on Strategies Adopted by Parents Who Use E-Cigarettes to Negotiate Risk Perceptions of Their Children's Secondhand Exposure and Parental Role Modeling.

Existing health messages mainly targeted youth susceptible to vaping or parents who do not have much knowledge about e-cigarettes. This study makes a unique contribution by conducting the first in-depth investigation of e-cigarette-using parents' risk perceptions and parental role modeling and how these two factors affect their vaping behaviors at home or implementation of any strategies to reduce their children's risk. Fifteen parents who used e-cigarettes participated in a semi-structured interview. Interview transcripts were coded and analyzed through a deductive approach of thematic analysis. This study demonstrates the need to develop and disseminate future health messages for e-cigarette-using parents who may have low-risk perceptions of secondhand exposure or who have adopted ineffective strategies to reduce their children's exposure. This study also identifies some possible targets for future intervention efforts through these parents including increasing their knowledge about the health risk of secondhand exposure to e-cigarettes, emphasizing the caregiver role, and effective communications with children about the consequences of vaping.

An ecological momentary assessment study to examine covariates and effects of concurrent and simultaneous use of electronic cigarettes and marijuana among college students.

INTRODUCTION: The prevalence of concurrent and simultaneous use of e-cigarette and marijuana among college students is high. Yet, the literature was mainly based on cross-sectional surveys with emphasis on the smoking route. This is the first ecological momentary assessment (EMA) study that examined the vaping route of nicotine-marijuana co-use and the associated short-term psychological effects. METHODS: This study recruited 686 college student e-cigarette users to participate in an on-line survey and 7-day EMA. Frequent marijuana users (247) - using marijuana weekly or daily - were compared with infrequent/non-users (439) on academic performance, e-cigarette use patterns, and dependence and respiratory symptoms. EMA data from the frequent users were used to study the association between marijuana vaping and e-cigarette consumption and the short-term psychological effects of e-cigarette and marijuana use. RESULTS: The results show that e-cigarette users who frequently used marijuana tended to have lower academic performance, be involved in higher-risk use patterns, and have higher levels of e-cigarette dependence, marijuana problems, and respiratory symptoms, compared to infrequent/non-users. Marijuana vaping was associated with a higher level of e-cigarette consumption. E-cigarette use and marijuana use were both associated with higher levels of positive affect, physiological sensation, and craving for e-cigarettes. While marijuana use was linked to a lower level of negative affect, e-cigarette use did not have a significant effect. Further, none of the interaction effects between e-cigarette and marijuana use on psychological states were significant. CONCLUSIONS: The results showed additive effects of e-cigarette and marijuana use although the hypothesized synergistic effects were not supported.

Subtypes of Dual Users of Combustible and Electronic Cigarettes: Longitudinal Changes in Product Use and Dependence Symptomatology.

INTRODUCTION: Cross-sectional surveys found behavioral heterogeneity among dual users of combustible and electronic cigarettes. Yet, prior classification did not reflect dynamic interactions between cigarette and e-cigarette consumption, which may reveal changes in product-specific dependence. The contexts of dual use that could inform intervention were also understudied. METHODS: This study conducted secondary analysis on 13 waves of data from 227 dual users who participated in a 2-year observational study. The k-means method for joint trajectories of cigarette and e-cigarette consumption was adopted to identify the subtypes of dual users. The time-varying effect model was used to characterize the subtype-specific trajectories of cigarette and e-cigarette dependence. The subtypes were also compared in terms of use contexts. RESULTS: The four clusters were identified: light dual users, predominant vapers, heavy dual users, and predominant smokers. Although heavy dual users and predominant smokers both smoked heavily at baseline, by maintaining vaping at the weekly to daily level the heavy dual users were able to considerably reduce cigarette use. Yet, the heavy dual users' drop in cigarette dependence was not as dramatic as their drop in cigarette consumption. Predominant vapers appeared to engage in substitution, as they decreased their smoking and increased their e-cigarette dependence. They were also more likely to live in environments with smoking restrictions and report that their use of e-cigarettes reduced cigarette craving and smoking frequency. CONCLUSIONS: Environmental constraints can drive substitution behavior and the substitution behavior is able to be sustained if people find the substitute to be effective. IMPLICATIONS: This study characterizes subtypes of dual users based on the dynamic interactions between cigarette use and e-cigarette use as well as product-specific trajectories of dependence. The subtypes differ in not only sociodemographic characteristics but also contexts of cigarette and e-cigarette use. Higher motivation to use e-cigarettes to quit smoking and less permissive environment for smoking may promote substitution of cigarettes by e-cigarettes.

Home e-cigarette rules and youth's vulnerability to initiate and sustain e-cigarette use.

Existing studies of the impact of home rules on youth's vulnerability to e-cigarette use were based on cross-sectional data, youth or parent reports alone, as well as youth's perceptions and susceptibility. This study capitalizes on the restricted-use data of the Population Assessment of Tobacco and Health (PATH) Study to examine the longitudinal association between home rules for e-cigarette use and youth's vulnerability including initiation of use and regular use two years later. Secondary analysis was conducted on 1203 parent-youth pairs who participated in both Wave 4 (2016-2018) and Wave 5 (2018-2019) assessment of the PATH Study and while the youth were age 12-16 at Wave 4. Linear and logistic regressions were performed to examine the associations between having a strict home rule for e-cigarette use at Wave 4 and the youth's outcomes including perceived social norms, expectancies, susceptibility, initiation of use, and regular use of e-cigarettes at Wave 5, controlling for parent and youth factors. The results show that having a strict home rule for e-cigarette use was associated with youth's heightened level of perceived injunctive norms (ß = 0.22, p < 0.01), higher expectancy of harmfulness (ß = 0.28, p < 0.01) and lower odds for regular e-cigarette use (OR = 0.36, p < 0.05). In conclusion, the findings of this study support the potential protective effects of implementing a strict home rule for e-cigarette use. Future intervention efforts may promote parents' awareness of the potential protective effects of a strict home e-cigarette rule on youth's normative belief, harm expectancy, and behavior of e-cigarette use.

Disposable E-Cigarettes and Associated Health Risks: An Experimental Study.

The use of electronic nicotine delivery systems (ENDS), including disposable e-cigarettes, has been prevalent. Existing chemical analyses of ENDS focused on e-liquids rather than aerosols and failed to consider particle sizes and aerosol respiratory deposition fractions, which are key factors for inhalation doses. This study investigated the organic chemical and metal constituents in size-segregated ENDS aerosol and assessed the deposited doses and health risks of these substances. Aerosol chemical analyses were conducted on two popular disposable ENDS products: Puff Bar (Grape) and Air Bar (Watermelon Ice). An ENDS aerosol was generated and delivered into a Micro-Orifice Uniform Deposit Impactor to collect size-segregated aerosol samples, in which organic chemicals and metals were analyzed. Daily and lifetime doses for each chemical were estimated. Cancer and non-cancer risk assessments were conducted based on the deposited doses. We found that e-cigarette aerosol contains certain harmful organic chemicals and metals documented to result in respiratory problems. Estimated respiratory cancer risks corresponding to chromium from both ENDS products and nickel from Air Bar (Watermelon Ice) were substantially above the conventionally acceptable risk. The method, findings, and implications can contribute to the extant literature of ENDS toxicity studies as well as inform tobacco regulation and future large-scale studies.

Alcohol and cannabis co-use and longitudinal gray matter volumetric changes in early and late adolescence.

BACKGROUND: Previous studies have characterized the impact of substance use on cerebral structure and function in adolescents. Yet, the great majority of prior studies employed a small sample, presented cross-sectional findings, and omitted potential sex differences. METHODS: Using data based on 724 adolescents (370 females) curated from the NCANDA study, we investigated how gray matter volumes (GMVs) decline longitudinally as a result of alcohol and cannabis use. The impacts of alcohol and cannabis co-use and how these vary across assigned sex at birth and age were examined. Brain imaging data comprised the GMVs of 34 regions of interest and the results were evaluated with a Bonferroni correction. RESULTS: Mixed-effects modeling showed faster volumetric declines in the caudal middle frontal cortex, fusiform, inferior frontal, superior temporal (STG), and supramarginal (SMG) gyri, at -0.046 to -0.138 cm3 /year in individuals with prior-year alcohol and cannabis co-use, but not those engaged in alcohol or cannabis use only. These findings cannot be explained by more severe alcohol use among co-users. Further, alcohol and cannabis co-use in early versus late adolescence predicted faster volumetric decline in the STG and SMG across assigned sex at birth. CONCLUSIONS: Findings highlight the longitudinal impact of alcohol and cannabis co-use on brain development, especially among youth reporting early adolescent onset of use. The volumetric decline was noted in cortical regions in support of attention, memory, executive control, and social cognition, suggesting the pervasive effect of alcohol and cannabis co-use on brain development.

The situational contexts and subjective effects of co-use of electronic cigarettes and alcohol among college students: An ecological momentary assessment (EMA) study.

INTRODUCTION: Understanding the co-use of e-cigarettes and alcohol, including the situational contexts and subjective effects associated with co-use in real-time is necessary for validating this behavior and informing intervention. Yet, the sparse literature has built upon retrospective data. METHODS: This study recruited 686 college students who were currently using e-cigarettes from three campuses in the Midwest and South of U.S in Fall 2019-Fall 2021. An on-line survey was conducted to measure e-cigarette use patterns, GPA, e-cigarette and alcohol dependence symptoms, and respiratory symptoms. A 7-day ecological momentary assessment was used to collect real-time data on e-cigarette and alcohol use, situational contexts and subjective effects. RESULTS: Frequent drinking e-cigarette users reported more high-risk use behavior including consuming 6 + drinks/occasion and simultaneous use, and reported more e-cigarettes and alcohol related dependence symptoms and respiratory symptoms, compared to infrequent/non-drinker e-cigarette users. Alcohol quantity was positively associated with e-cigarette quantity among the high frequency drinking group. This study identified important use contexts that were associated with higher e-cigarette consumption including use of menthol or fruit flavored e-cigarettes, being in a car, and the presence of others. E-cigarette use and alcohol use both increased the levels of positive affect, physiological sensation, and craving for e-cigarettes, whereas only alcohol use significantly decreased negative affect. No interaction effects between e-cigarette use and alcohol use were found. CONCLUSIONS: The findings highlight the addiction and health risks associated with frequent co-use of e-cigarettes and alcohol, and also call for regulations on nontobacco flavorings in e-cigarette products.

Characteristics of statewide prescription drug monitoring programs and potentially inappropriate opioid prescribing to patients with non-cancer chronic pain: A machine learning application.

Unnecessary/unsafe opioid prescribing has become a major public health concern in the U.S. Statewide prescription drug monitoring programs (PDMPs) with varying characteristics have been implemented to improve safe prescribing practice. Yet, no studies have comprehensively evaluated the effectiveness of PDMP characteristics in reducing opioid-related potentially inappropriate prescribing (PIP) practices. The objective of the study is to apply machine learning methods to evaluate PDMP effectiveness by examining how different PDMP characteristics are associated with opioid-related PIPs for non-cancer chronic pain (NCCP) treatment. This was a retrospective observational study that included 802,926 adult patients who were diagnosed NCCP, obtained opioid prescriptions, and were continuously enrolled in plans of a major U.S. insurer for over a year. Four outcomes of opioid-related PIP practices, including dosage ≥50 MME/day and ≥90 MME/day, days supply ≥7 days, and benzodiazepine-opioid co-prescription were examined. Machine learning models were applied, including logistic regression, least absolute shrinkage and selection operation regression, classification and regression trees, random forests, and gradient boost modeling (GBM). The SHapley Additive exPlanations (SHAP) method was applied to interpret model results. The results show that among 1,886,146 NCCP opioid-related claims, 22.8% had an opioid dosage ≥50 MME/day and 8.9% ≥90 MME/day, 70.3% had days supply ≥7 days, and 10.3% were when benzodiazepine was filled ≤7 days ago. GBM had superior model performance. We identified the most salient PDMP characteristics that predict opioid-related PIPs (e.g., broader access to patient prescription history, monitoring Schedule IV controlled substances), which could be informative to the states considering the redesign of PDMPs.

A new statistical model for longitudinal ecological momentary assessment data on dual use of electronic and combustible cigarettes.

Background: Existing studies of dual use of electronic and combustible cigarettes either collected longitudinal data with long gaps in between waves or conducted ecological momentary assessment (EMA) over a short period of time. In recent years, the measurement burst design that embeds an EMA protocol in each wave assessment of a traditional longitudinal study has become more popular and yet conventional generalized linear mixed models (GLMM) have important limitations for handling data from this design.Objectives: This study proposed a new statistical method to analyze data from the measurement burst design.Methods: This new statistical method was designed to model the short-term (within-wave) as well as long-term (between-wave) changes and was validated by a simulation study. Secondary analysis was conducted to analyze data from 205 dual users (52% male) and 146 exclusive smokers (50% male) who participated in a recent study using the measurement burst design.Results: The simulation study shows that the proposed method can handle the gap between waves well and is also robust to nonlinear changes across waves. Although no short-term change in smoking was found, dual users reported a long-term reduction in cigarette use that was more rapid compared to exclusive smokers (߈=-0.0127,p=.0167). Vaping more was associated with smoking less (߈=-0.0058,p=.0054).Conclusion: The proposed method is highly applicable as it can be easily implemented by substance use researchers and the results can be straightforwardly interpreted. The results suggest that e-cigarette use may play a role in promoting a long-term reduction in smoking among dual users.

Polygenic risk prediction based on singular value decomposition with applications to alcohol use disorder.

BACKGROUND/AIM: The polygenic risk score (PRS) shows promise as a potentially effective approach to summarize genetic risk for complex diseases such as alcohol use disorder that is influenced by a combination of multiple variants, each of which has a very small effect. Yet, conventional PRS methods tend to over-adjust confounding factors in the discovery sample and thus have low power to predict the phenotype in the target sample. This study aims to address this important methodological issue. METHODS: This study proposed a new method to construct PRS by (1) approximating the polygenic model using a few principal components selected based on eigen-correlation in the discovery data; and (2) conducting principal component projection on the target data. Secondary data analysis was conducted on two large scale databases: the Study of Addiction: Genetics and Environment (SAGE; discovery data) and the National Longitudinal Study of Adolescent to Adult Health (Add Health; target data) to compare performance of the conventional and proposed methods. RESULT AND CONCLUSION: The results show that the proposed method has higher prediction power and can handle participants from different ancestry backgrounds. We also provide practical recommendations for setting the linkage disequilibrium (LD) and p value thresholds.

The Protective Effects of Social Support on Hypertension Among African American Adolescents Exposed to Violence.

African Americans develop hypertension earlier in life than Whites and the racial/ethnic disparities in blood pressure level can appear as early as adolescence. Violence victimization, a prevalent environmental stressor among inner-city youth, may play a role in such disparities. In a sample of inner-city youth in the United States, the current study examines the relationship between violence victimization and hypertension while investigating the role of social support in moderating that relationship. We analyzed eight waves of data from a longitudinal study of African American youth (n = 353, 56.7% female) from mid-adolescence (9th grade, mean age = 14.9 years old) to emerging adulthood (mean age = 23.1 years old) using probit regression. Higher levels of self-reported violence victimization during ages 14-18 was associated with more reports of hypertension during ages 20-23, after adjusting for sex, socioeconomic status, substance use, and mental distress. The relationship of violence victimization with hypertension was moderated by friends' support, but not parental support. The association between victimization and hypertension was weaker and non-significant among individuals with more peer support compared to those with less support. Researchers have reported many instances of associations of early violence exposure to later risk for hypertension; however, most have focused on childhood maltreatment or intimate partner violence. We extend these findings to violence victimization in an African American sample of youth from adolescence to early adulthood, while examining social support modifiers. The disparity in African American hypertension rates relative to Whites may partly be explained by differential exposure to violence. Our findings also suggest that having supportive friends when faced with violence can be beneficial for young adulthood health outcomes.

Chronic pain and delinquency partially explain the effect of the DRD4 gene polymorphism on adult substance use.

Background: The dopamine receptor D4 [DRD4] has been reported to be associated with substance use. Yet, the roles that health conditions and behaviors may play in such association are understudied.Objective: This longitudinal study investigated the potential mediation effects of chronic pain and delinquency in adolescence on the association between the DRD4 2-repeat allele and substance use in adulthood. Sex, witnessing violence, and experiencing violence were also examined as potential moderators for the mediation pathways.Methods: We used the restricted and candidate gene data from the National Longitudinal Study of Adolescent to Adult Health (Waves I-IV) to conduct secondary analysis (N = 8,671; 47% male). A two-step approach was adopted to examine the mediation effects regarding four substance use outcomes in adulthood: number of lifetime alcohol use disorder symptoms, lifetime regular smoker status, past-month smoking, and lifetime "pain killer" misuse. The moderation effects were investigated using stratification and permutation.Results: The DRD4 2-repeat allele was associated with all adulthood substance use outcomes through adolescent chronic pain and delinquency (AORs/IRR range 1.08-3.78; all ps<0.01). The association between delinquency and smoking was higher among females. The association between delinquency and substance use was lower among the participants who witnessed violence in adolescence.Conclusions: This study identified modifiable mediators underlying the association between the DRD4 2-repeat allele and substance use behaviors, concluding that chronic pain and delinquency partially explain the effect of the DRD4 gene polymorphism on adult substance use.

Estimation of the dose of electronic cigarette chemicals deposited in human airways through passive vaping.

BACKGROUND: Existing studies on the health effects of e-cigarettes focused on e-cigarette users themselves. To study the corresponding effects on passive vapers, it is crucial to quantify e-cigarette chemicals deposited in their airways. OBJECTIVE: This study proposed an innovative approach to estimate the deposited dose of e-cigarette chemicals in the passive vapers' airways. The effect of the distance between active and passive vapers on the deposited dose was also examined. METHODS: The chemical constituent analysis was conducted to detect Nicotine and flavoring agents in e-cigarette aerosol. The Mobile Aerosol Lung Deposition Apparatus (MALDA) was employed to conduct aerosol respiratory deposition experiments in real-life settings to generate real-time data. RESULTS: For e-cigarette aerosol in the ultrafine particle regime, the deposited doses in the alveolar region were on average 3.2 times higher than those in the head-to-TB airways, and the deposited dose in the passive vaper's airways increased when being closer to the active vaper. SIGNIFICANCE: With prolonged exposure and close proximity to active vapers, passive vapers may be at risk for potential health effects of harmful e-cigarette chemicals. The methodology developed in this study has laid the groundwork for future research on exposure assessment and health risk analysis for passive vaping.