Addictive behaviors最新文献

Background

The incidence of behavioral addictions (BAs) associated with scientific and technological advances has been increasing steadily. Unfortunately, a large number of studies on the structural and functional abnormalities have shown poor reproducibility, and it remains unclear whether different addictive behaviors share common underlying abnormalities. Therefore, our objective was to conduct a quantitative meta-analysis of different behavioral addictions to provide evidence-based evidence of common structural and functional changes.

Methods:

We conducted systematic searches in PubMed, Web of Science and Scopus from January 2010 to December 2023, supplementing reference lists of high-quality relevant meta-analyses and reviews, to identify eligible voxel-based morphometry (VBM) and functional magnetic resonance imaging (fMRI) studies. Using anisotropic seed-based D-Mapping (AES-SDM) meta-analysis methods, we compared brain abnormalities between BAs and healthy controls (HCs).

Results

There were 11 GMV studies (287 BAs and 292 HCs) and 26 fMRI studies (577 BAs and 545 HCs) that met inclusion criteria. Compared with HCs, BAs demonstrated significant reductions in gray matter volume (GMV) in (1) right anterior cingulate gyri extending into the adjacent superior frontal gyrus, as well as in the left inferior frontal gyrus and right striatum. (2) the bilateral precuneus, right supramarginal gyrus, and right fusiform gyrus were hyperfunction; (3) the left medial cingulate gyrus extended to the superior frontal gyrus, the left inferior frontal gyrus, and right middle temporal gyrus had hypofunction.

Conclusions

Our study identified structural and functional impairments in brain regions involved in executive control, cognitive function, visual memory, and reward-driven behavior in BAs. Notably, fronto-cingulate regions may serve as common biomarkers of BAs.

Background

Interest in characterizing individuals involved in addictive behaviors has been growing, which allows tailoring prevention and intervention strategies to the gambler’s needs. The study aimed to 1) identify clusters of gamblers according to gambling-related characteristics and mental health; and 2) analyze differences in psychological variables between the clusters. Methods. A total of 83 participants undergoing treatment for gambling disorder (M_age = 45.52, 51.8 % female) completed a set of questionnaires. Hierarchical cluster analysis was performed to classify gambling based on gambling variables (i.e., gambling severity and gambling motives) and mental health (i.e., depression, anxiety, and hostility). Several ANOVAs were conducted to illustrate the distinguishing features of each cluster, encompassing both the variables included in the cluster analysis and other relevant psychological variables. Results. Findings suggest that gamblers can be classified into three clusters based on these variables: 1) “high gambling severity and good mental health,” 2) “high gambling severity and poor mental health,” and 3) “low gambling severity and good mental health.” These clusters were differentiated as a function of psychological variables, such as emotional dependence, alexithymia, and stressful life events. Conclusions. Classifying gamblers according to their profile provides a better understanding of their needs and problems, allowing for a more tailored approach in terms of prevention and intervention strategies.

Introduction

Little is known about the influence of e-cigarette marketing on cannabis vaping behaviors. This study examined the associations between e-cigarette marketing exposure and nicotine and cannabis vaping among adults.

Methods

This cross-sectional study included a U.S. nationally representative sample of adults from the Wave 6 survey of the Population Assessment of Tobacco and Health Study. We used multinomial logistic regressions to examine the associations between past 30-day e-cigarette marketing exposure and past 30-day vaping behavior (sole- and dual-vaping of nicotine and cannabis) overall and stratified by age.

Results

Overall, 52.0 % of respondents reported e-cigarette marketing exposure, and 89.8 %, 5.6 %, 3.2 %, and 1.4 % reported no vaping, sole-nicotine vaping, sole-cannabis vaping, and dual-vaping, respectively. E-cigarette marketing exposure was associated with increased odds of reporting sole-cannabis vaping versus no vaping (adjusted risk ratio [aRR], 1.31; 95 % confidence interval [CI], 1.09–1.57) and dual-vaping versus no vaping (aRR, 1.26; 95 % CI, 1.01–1.57). This association was found among those aged 18–24 and 25–34 years. It was also associated with increased odds of reporting sole-cannabis vaping versus sole-nicotine vaping (aRR, 1.28; 95 % CI, 1.04–1.58). This association was found among those aged 18–24 years.

Discussion

E-cigarette marketing exposure was associated with sole-cannabis vaping and dual-vaping, not sole-nicotine vaping among U.S. adults. Such associations were mainly driven by young adults aged 18–24 and 25–34 years. Greater restrictions on tobacco marketing may have reduced the influence of e-cigarette marketing on nicotine vaping, while gaps in marketing restrictions for cannabis may contribute to e-cigarette marketing influence on cannabis vaping.

Background

In November 2019, the Massachusetts legislature passed An Act Modernizing Tobacco Control and became the first state to restrict retail sales of all flavored (including menthol) cigarettes, e-cigarettes, and other tobacco products. Our study aims to provide the retailer experience of the new law from the perspectives of multiple stakeholders, including tobacco retailers themselves, public health officials, and Massachusetts residents.

Methods

We conducted in-depth interviews with seven tobacco retailers and ten public health officials from March 2021 to April 2022. Monthly repeated cross-sectional surveys were administered through the online survey panel Prodege from April 2021 to August 2022 (adult sample: N = 765; adolescent sample: N = 900). Themes from interviews were identified by drawing on deductive codes informed by the interview guide, followed by inductive coding of data. Survey data were descriptively analyzed in R.

Results

Key themes included retailer frustration over loss of sales to neighboring states, factors associated with retailer compliance, and the need for increased education regarding the law. Survey results showed that a minority of adolescents (13.3%) and adults (26.1%) who vaped in the past 30-days were traveling to border states to purchase vape products. Less than one-quarter of adolescent participants and less than half of adult participants could correctly identify which products Massachusetts did not sell.

Conclusions

Evidence from the retailer, public health, and end-user perspectives support mutual benefits of adjacent states enacting flavored tobacco sales restrictions, improved policy education for retailers and the public, and improved retailer enforcement.

Despite declines in adolescent nicotine vaping during the COVID-19 pandemic, vaping continues to be a public health issue for many adolescents. Most studies on teen reasons for vaping and on barriers and facilitators of vaping were conducted prior to the pandemic. Because teen culture changes so rapidly, and because the pandemic had wide-reaching effects on teens and mental health, it is critical to have a current understanding what helps adolescents to quit vaping (facilitators), as well as what prevents them from quitting (barriers) in order to design effective and engaging interventions. The objective of this qualitative study was to examine reasons for vaping, and barriers and facilitators to quitting vaping among high school age (14–18 years old) students. Students (n = 28; 60.7 % female; 50 % White, 10.7 % Black or African American, 25 % Asian or Asian American, 3.6 % other non-Hispanic; 7.2 % Hispanic; 21.4 % former vapers, 78.6 % current vapers) were recruited online from four regions in the US and participated in one of five online focus groups. We conducted a content analysis of the focus groups using a team-based coding approach. The most frequently cited reasons for vaping were mood, peer influence, and boredom. Results also showed that the stigma of seeking treatment acted as a barrier to quitting vaping, while self-reflection acted as a facilitator. In addition, two factors, peer influence and health effects, served as both barriers and facilitators, depending on the context. Program developers can use this information to design engaging vaping cessation programs intended for adolescents.

Background

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.

Methods

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).

Conclusions

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.

Substance use disparities among sexual and gender minority (SGM) people are attributed to minority stress, but few studies have examined minority stress and cannabis use over time or investigated differences in cannabis use trajectories by less-studied gender subgroups. We examined if longitudinal cannabis use trajectories are related to baseline minority stressors and if gender differences persisted after accounting for minority stress. Cannabis use risk was measured annually over four years (2017–2021) within a longitudinal cohort study of SGM adults in the United States (N = 11,813). Discrimination and victimization, internalized stigma, disclosure and concealment, and safety and acceptance comprised minority stress (n = 5,673). Latent class growth curve mixture models identified five cannabis use trajectories: ‘low or no risk’, ‘low moderate risk’, ‘high moderate risk’, ‘steep risk increase’, and ‘highest risk’. Participants who reported past-year discrimination and/or victimization at baseline had greater odds of membership in any cannabis risk category compared to the ‘low risk’ category (odds ratios [OR] 1.17–1.33). Internalized stigma was related to ‘high moderate’ and ‘highest risk’ cannabis use (ORs 1.27–1.38). After accounting for minority stress, compared to cisgender men, gender expansive people and transgender men had higher odds of ‘low moderate risk’ (ORs 1.61, 1.67) or ‘high moderate risk’ (ORs 2.09, 1.99), and transgender men had higher odds of ‘highest risk’ (OR 2.36) cannabis use. This study indicates minority stress is related to prospective cannabis use risk trajectories among SGM people, and transgender men and gender expansive people have greater odds of trajectories reflecting cannabis use risk.

Introduction

This study assessed quit attempts among adults who use cigarettes either exclusively or with e-cigarettes in Mexico, where non-daily smoking predominates.

Methods

An open cohort of Mexican adults who smoke was surveyed every four months from November 2018 to March 2021. Participants followed to the next survey were analyzed (n = 2220 individuals, 4560 observations). Multinomial logistic models regressed smoking quit attempts reported at the followup survey (ref = no attempt; tried to quit; sustained attempt of ≥30 days) on e-cigarette use frequency (none = ref; 1–2 days/week; ≥3 days/week), adjusting for sociodemographics and smoking-related variables. Additional models subdivided e-cigarette users by intentions to quit smoking in the next six months (i.e., yes/no), use of nicotine (i.e., yes/no), and vaping device used (i.e., open/closed).

Results

At 4-month follow-up, 32.7 % had tried to quit, and 2.9 % had quit for 30 days or more. Compared to those who smoke exclusively, occasional, and frequent e-cigarette users were more likely to try to quit (Adjusted Relative Risk Ratio or ARRR = 1.26 and 1.66, respectively) but no more likely to sustain their quit attempt. Among those who intended to quit smoking, e-cigarette users were no more likely to either try or sustain quit attempts. Furthermore, use of e-cigarettes with nicotine (59.6 %) was unassociated with cessation except that those who frequently used e-cigarettes with nicotine were more likely to try to quit than those who smoke exclusively (ARRR = 1.88). Device type used was not differentially associated with outcomes.

Conclusions

Mexicans who smoke and use e-cigarettes appear more likely than those who smoke exclusively to try to quit but not to sustain abstinence.

Background

Few studies examine the relationship between depression and use of specific tobacco and/or cannabis products among adolescents, young adults, and adults. We determined whether the odds of depression are greater among those who used specific tobacco and/or cannabis products and among co-users of tobacco and cannabis.

Method

Cross-sectional online survey of a national convenience sample of 13–40-year-olds (N = 6,038). The survey included depression screening and past 30-day use of specific tobacco and cannabis products (cigarettes; e-cigarettes, vaped cannabis, little cigars, cigarillos, cigars, hookah, chewing tobacco, smoked cannabis, edible cannabis, blunts). Analyses correspond to the total sample, and 13–17-, 18–24-, and 25–40-year-olds.

Results

Among 5,281 individuals who responded to the depression screener and nine product use questions, 1,803 (34.1 %) reported co-use of at least one tobacco product and one cannabis product in the past 30 days. Past 30-day co-use was associated with higher likelihood of screening positive for depression compared to past 30-day use of tobacco-only (aOR = 1.32, 1.06–1.65; 0.006) or cannabis-only (aOR = 1.94, 1.28–2.94; <0.001). Screening positive for depression was more likely among those who reported past 30-day use of e-cigarettes (aOR = 1.56; 1.35–1.80; <0.001), cigarettes (aOR = 1.24, 1.04–1.48; 0.016), chewed tobacco (aOR = 1.91, 1.51–2.42; <0.001), and blunts (aOR = 1.22, 1.00–1.48; 0.053) compared to those who did not report past 30-day use of these products. Among the 2,223 individuals who screened positive for depression, the most used two-product combination was nicotine e-cigarettes and smoked cannabis (614 individuals, 27.6 %).

Conclusions

Screening positive for depression was more likely among past 30-day co-users versus past 30-day users of tobacco-only or cannabis-only. Findings suggest that prevention programs for depression and substance use address tobacco and cannabis co-use.

Background

Electronic (e-)cigarettes may help adult cigarette smokers achieve cigarette cessation, depending on patterns of e-cigarette use. Among cigarette smokers who do not use e-cigarettes, it is unclear if and how a-priori intentions for use are related to uptake patterns. Longitudinal studies have focused on established e-cigarette users or adolescent and young adult populations exclusively.

Methods

Within a nationwide randomized clinical trial (N = 638), adult cigarette smokers not currently using e-cigarettes were randomized (2:1) to receive (or not) one-month sampling of e-cigarettes. An exploratory factor analysis (EFA) was performed on an established 15-item measure assessing a-priori intentions for e-cigarette use to identify latent variables. Among those receiving e-cigarette products, regression models examined relationships between intentions and: 1) uptake (yes/no), 2) frequency (number of days per week), and 3) amount (puffing episodes per day) of e-cigarette use at one-month follow-up.

Results

Two factors emerged from the EFA: 1) cigarette-related intentions (e.g., cigarette cessation, no smell) and 2) novel appeal of e-cigarettes (e.g., flavors). Three items remained and were treated as separate intentions: “feels like cigarette smoking”, “curiosity”, and “affordability“. In the final multivariable models, “feel like cigarette smoking” predicted more frequent e-cigarette use (β = 0.187, SE = 0.086, p = 0.03); however, none of the five factors/intentions were significantly associated with uptake or amount of use.

Conclusions

For adult cigarette smokers not currently using e-cigarettes, a-priori intentions for using e-cigarettes might not be predictive of if or how these products will be used in the future, suggesting that motives may not drive use behavior.