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The extent to which vaping influences depression is unclear, but could be estimated through application of novel epidemiologic methods. Among a prospective cohort of young adults from California who screened negative for depression, we estimated repeated measures marginal structural models to examine the association of four vaping transitions from time T to T+1 (persistent use, discontinuation, initiation, persistent nonuse) with risk of clinically significant depressive symptoms at T+1, simultaneously across three ~1.5 year time-intervals between 2017-2021. Stabilized inverse probability of treatment and censoring weights adjusted for time-dependent confounders and selection bias. Among n=3,496 observations (1,806 participants, mean pooled baseline age=19.5), 8.1% reported persistent vaping from T to T+1, 6.2% reported discontinuation (i.e., use at T and no use at T+1), 6.5% initiated e-cigarettes (i.e., no use at T and use at T+1), and 79.2% reported persistent nonuse at both time-points. Compared to persistent vaping at two waves, persistent nonuse (RR=0.76, 95%CI:0.62-0.93) and discontinuation (RR=0.71, 95%CI:0.52-0.96) were associated with lower risk of depression. Associations were robust to sensitivity analyses, including restricting to tobacco naïve participants and varying temporal assumptions to reduce potential for reverse causation. Young adults who consistently avoid or discontinue vaping may be protected from depressive symptom occurrence.
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OBJECTIVE: While e-cigarette use is associated with adverse cardiopulmonary health effects, the mortality risks associated with e-cigarette use alone and combined with smoking remain unexamined. METHODS: Data between 2014 and 2018 were obtained from the National Health Interview Survey (NHIS), an annual cross-sectional survey of US adults. All-cause mortality and date of death were obtained via linkage of the NHIS to the National Death Index through December 31, 2019. A 6-category composite cigarette (never, former, current) and e-cigarette (current, non-current) exposure variable was created. We examined the association of cigarette and e-cigarette use patterns with all-cause mortality using adjusted Cox models. RESULTS: Among 145,390 participants (79,294 women [51.5%]; 60,560 aged 18-44 [47.4%]), 5220 deaths were observed over a median follow-up of 3.5 years (508,545 total person-years). Dual use of cigarettes and e-cigarettes was associated with higher mortality risk compared with non-current e-cigarette use in combination with never smoking (hazard ratio [HR] 2.44; 95% CI, 1.90-3.13) and had a risk that did not differ from current exclusive smoking (HR, 1.06; 95% CI, 0.83-1.37). Current e-cigarette use in combination with former smoking was associated with a lower mortality risk than current exclusive cigarette smoking (HR 0.64; 95% CI, 0.41-0.99). CONCLUSIONS: The addition of e-cigarette use to smoking does not reduce mortality risk compared with exclusive smoking. However, transitioning completely from cigarettes to e-cigarettes may be associated with mortality risk reduction. Further research is needed to verify these findings in larger cohorts and over longer periods of follow-up.
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Importance: After the initial disruption from the COVID-19 pandemic, it is unclear how patterns of e-cigarette use in the US have changed. Objective: To examine recent patterns in current and daily e-cigarette use among US adults in 2021. Design, Setting, and Participants: This cross-sectional study used data from the 2021 Behavioral Risk Factor Surveillance System (BRFSS) database. The BRFSS is the largest national telephone-based survey of randomly sampled adults in the US. Adults aged 18 years or older, residing in 49 US states (all except Florida), the District of Columbia, and 3 US territories (Guam, Puerto Rico, and the US Virgin Islands), were included in the data set. Data analysis was performed in January 2023. Main Outcomes and Measures: The main outcome was age-adjusted prevalence of current and daily e-cigarette use overall and by participant characteristics, state, and territory. Descriptive statistical analysis was conducted, applying weights to account for population representation. Results: This study included 414â¯755 BRFSS participants with information on e-cigarette use. More than half of participants were women (51.3%). In terms of race and ethnicity, 0.9% of participants were American Indian or Alaska Native, 5.8% were Asian, 11.5% were Black, 17.3% were Hispanic, 0.2% were Native Hawaiian or Other Pacific Islander, 62.2% were White, 1.4% were of multiple races or ethnicities, and 0.6% were of other race or ethnicity. Individuals aged 18 to 24 years comprised 12.4% of the study population. The age-standardized prevalence of current e-cigarette use was 6.9% (95% CI, 6.7%-7.1%), with almost half of participants using e-cigarettes daily (3.2% [95% CI, 3.1%-3.4%]). Among individuals aged 18 to 24 years, there was a consistently higher prevalence of e-cigarette use, with more than 18.6% reporting current use and more than 9.0% reporting daily use. Overall, among individuals reporting current e-cigarette use, 42.2% (95% CI, 40.7%-43.7%) indicated former combustible cigarette use, 37.1% (95% CI, 35.6%-38.6%) indicated current combustible cigarette use, and 20.7% (95% CI, 19.7%-21.8%) indicated never using combustible cigarettes. Although relatively older adults (aged ≥25 years) who reported current e-cigarette use were more likely to report former or current combustible cigarette use, younger adults (aged 18-24 years) were more likely to report never using combustible cigarettes. Notably, the proportion of individuals who reported current e-cigarette use and never using combustible cigarettes was higher in the group aged 18 to 20 years (71.5% [95% CI, 66.8%-75.7%]) compared with those aged 21 to 24 years (53.0% [95% CI, 49.8%-56.1%]). Conclusion and Relevance: These findings suggest that e-cigarette use remained common during the COVID-19 pandemic, particularly among young adults aged 18 to 24 years (18.3% prevalence). Notably, 71.5% of individuals aged 18 to 20 years who reported current e-cigarette use had never used combustible cigarettes. These results underscore the rationale for the implementation and enforcement of public health policies tailored to young adults.
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COVID-19 , Sistemas Eletrônicos de Liberação de Nicotina , Vaping , Adulto Jovem , Humanos , Feminino , Idoso , Masculino , Sistema de Vigilância de Fator de Risco Comportamental , Vaping/epidemiologia , Estudos Transversais , Pandemias , COVID-19/epidemiologiaRESUMO
While the impact of combustible cigarette smoking on cardiovascular disease (CVD) is well-established, the longitudinal association of non-traditional tobacco products with subclinical and clinical CVD has not been fully explored due to: 1) limited data availability; and 2) the lack of well-phenotyped prospective cohorts. Therefore, there is the need for sufficiently powered well-phenotyped datasets to fully elucidate the CVD risks associated with non-cigarette tobacco products. The Cross-Cohort Collaboration (CCC)-Tobacco is a harmonized dataset of 23 prospective cohort studies predominantly in the US. A priori defined variables collected from each cohort included baseline characteristics, details of traditional and non-traditional tobacco product use, inflammatory markers, and outcomes including subclinical and clinical CVD. The definitions of the variables in each cohort were systematically evaluated by a team of two physician-scientists and a biostatistician. Herein, we describe the method of data acquisition and harmonization and the baseline sociodemographic and risk profile of participants in the combined CCC-Tobacco dataset. The total number of participants in the pooled cohort is 322782 (mean age: 59.7 ± 11.8 years) of which 76% are women. White individuals make up the majority (73.1%), although there is good representation of other race and ethnicity groups including African American (15.6%) and Hispanic/Latino individuals (6.4%). The prevalence of participants who never smoked, formerly smoked, and currently smoke combustible cigarettes is 50%, 36%, and 14%, respectively. The prevalence of current and former cigar, pipe, and smokeless tobacco is 7.3%, 6.4%, and 8.6%, respectively. E-cigarette use was measured only in follow-up visits of select studies, totaling 1704 former and current users. CCC-Tobacco is a large, pooled cohort dataset that is uniquely designed with increased power to expand knowledge regarding the association of traditional and non-traditional tobacco use with subclinical and clinical CVD, with extension to understudied groups including women and individuals from underrepresented racial-ethnic groups.
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Surveillance of e-cigarette use among different population groups is important for the timely implementation and evaluation of tobacco regulatory policies. In this review, we identified 13 nationally representative, repeatedly conducted epidemiologic surveys that assess e-cigarette use among U.S. youth and/or adults and have been instrumental in e-cigarette surveillance. These surveys included National Youth Tobacco Survey, Youth Risk Behavior Surveillance System, Monitoring the Future Survey, International Tobacco Control Policy Evaluation Project (ITC) Youth Tobacco and Vaping Survey, Behavioral Risk Factor Surveillance System, National Health Interview Survey, Tobacco Use Supplement of the Current Population Survey, Health Information National Trends Survey, Tobacco Products and Risk Perception Surveys, ITC Four Country Smoking and Vaping Survey, National Health and Nutrition Examination Survey, National Survey on Drug Use and Health, and Population Assessment of Tobacco and Health. These surveys vary in scope and detail, with their unique strengths and the regulatory questions that can be answered using each survey data. We also highlighted the gaps in these surveys and made recommendations for improvement.
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BACKGROUND: This study explores the association between psychosocial stressors and current e-cigarette use among adolescents in the United States. METHODS: We used data from 12,767 participants in the 2019 National Youth Risk Behavioral Survey to examine the association between psychosocial stressors (bullying, sexual assault, safety-related absence from school, depressive symptoms, suicidal ideation, physical altercation, and weapon threats) and past-30-day e-cigarette use using multivariable-adjusted logistic regression models. We examined the association for each stressor and then as a burden score (0-7). To compare the strength of the association between stressors and current e-cigarette use to current combustible cigarette use, we additionally examined the association between each stressor and current combustible cigarette use. RESULTS: Approximately 32.7% reported current e-cigarette use. The weighted prevalence of current e-cigarette use was higher among individuals who experienced stressors than those who did not. For example, bullying (43.9% vs. 29.0%). Similar prevalence patterns were seen among other stressors. Individuals who experienced stressors had significantly higher adjusted odds of current e-cigarette use than those who did not (OR [Odds Ratio] range: 1.47-1.75). Similarly, individuals with higher burden scores had a higher prevalence (zero [20.5%], one [32.8%], two [41.4%], three [49.6%], four to seven [60.9%]) and higher odds of current e-cigarette use (OR range: 1.43-2.73) than those with a score of zero. The strength of the association between the stressors and e-cigarette use was similar to that between the stressors and combustible cigarette use. CONCLUSION: The study demonstrates a significant association between psychosocial stressors and adolescent e-cigarette use, highlighting the potential importance of interventions, such as targeted school-based programs that address stressors and promote stress management, as possible means of reducing adolescent e-cigarette use. Future research directions include exploring underlying mechanisms linking stressors to e-cigarette use and evaluating the effectiveness of interventions addressing stressors in reducing adolescent e-cigarette use.
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Sistemas Eletrônicos de Liberação de Nicotina , Vaping , Humanos , Adolescente , Estados Unidos/epidemiologia , Vaping/epidemiologia , Inquéritos e Questionários , Assunção de Riscos , Ideação SuicidaRESUMO
Menthol cigarettes have had a profound adverse effect on public health. On 1 June 2020, Massachusetts became the first state to ban the sale of menthol cigarettes. We explored how perceptions of the ban and smoking behaviors changed over time among a group of 27 individuals who smoked menthol cigarettes at our safety-net hospital. In a convergent mixed methods study, we administered questionnaires and interviews simultaneously at two timepoints: 1 month pre-ban and 6 months post-ban. Pre-ban, we assessed perceptions of the ban and anticipated smoking behaviors after the ban. Post-ban, we assessed participants' actual smoking behaviors and elicited suggestions to avoid unintended consequences that might undermine intended policy effects. Several respondents perceived the Massachusetts ban as positive because it could promote smoking cessation, prevent youth initiation, and mitigate unfair targeting of socioeconomically disadvantaged populations. Others perceived the ban as an overreach of government policy, financially motivated, and unfairly targeting the Black community. Many continued to smoke menthol cigarettes obtained outside Massachusetts. Individuals suggested promoting tobacco treatment for people affected by the ban and a national ban to circumvent out-of-state purchasing of menthol cigarettes. Our findings suggest that in order to be most effective, healthcare systems must promote tobacco treatment and ensure that treatment is accessible to all individuals affected by the ban.
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Mentol , Produtos do Tabaco , Adolescente , Humanos , Estudos Longitudinais , Massachusetts , Fumar/epidemiologiaRESUMO
Among adolescents, sole use is the most common pattern of e-cigarette use. However, concurrent use of e-cigarettes with other tobacco products is not uncommon and may be associated with high-risk behaviors. We used data from 12,767 participants in the 2019 Youth Risk Behavior Survey to examine the patterns of tobacco product use among youth in the US. First, we examined the prevalence of e-cigarette-specific patterns of tobacco use (nonuse[no tobacco product use], sole use[sole e-cigarette use], dual-use[e-cigarette and one other tobacco product], and poly use[e-cigarette and two or more other tobacco products]). Then, using multivariable Poisson regression, we assessed how the tobacco use patterns were associated with the misuse of nine substances of abuse (alcohol, marijuana, cocaine, ecstasy, hallucinogens, heroin, inhalants, injectables, and methamphetamines). 62.9% of youth reported nonuse of any tobacco product. The weighted prevalence of sole e-cigarette use, dual use, and poly use was 23.2%, 4.2%, and 3.3%, respectively. Across all the substances explored, the prevalence was highest among poly users, followed by dual users, sole users, and non-users. Compared to non-users, sole, dual, and poly users had 7.8(95 %CI:6.1-10.0), 14.3(95 %CI:10.8-18.8), and 19.7(95 %CI:15.0-25.9) times higher adjusted prevalence of reporting past-30-day binge drinking, after adjusting for age, sex, race/ethnicity, sexual orientation, and depressive symptoms. This pattern was seen across all the different substances explored. These findings highlight the high prevalence of substance misuse among youth who use tobacco products and the need to educate and counsel on substances of abuse among this population, particularly among poly-tobacco users.
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INTRODUCTION: This study aimed to evaluate socioeconomic and racial/ethnic differences in e-cigarette uptake and harm perceptions about e-cigarettes among adults who smoke cigarettes in the U.S. METHODS: Five waves of the U.S. Population Assessment of Tobacco and Health Study (2013-2019) were used to assess transitions from exclusive cigarette smoking to (1) exclusive e-cigarette use, (2) dual use, and (3) nonuse of either product (N=7,172). Analyses (conducted in 2022) estimated differences in transitions and e-cigarette harm perceptions by race/ethnicity, income, and education. RESULTS: Hispanic (OR=0.32; 95% CI=0.18, 0.54) and Black (OR=0.38; 95% CI=0.22, 0.65) adults were less likely than White adults to transition from exclusive cigarette to exclusive e-cigarette use after 1 year. Adults with a bachelor's degree (versus those with less than high school) (OR=2.57; 95% CI=1.49, 4.45) and adults making ≥$100,000/year (versus those making <$10,000) (OR=3.61; 95% CI=2.10, 6.22) were more likely to transition from exclusive cigarette to exclusive e-cigarette use. Hispanic and Black adults and those with lower income and education were more likely to perceive e-cigarettes as equally or more harmful than cigarettes, which in turn was associated with lower odds of transitioning from exclusive cigarette smoking to exclusive e-cigarette use (OR=0.62; 95% CI=0.47, 0.81). CONCLUSIONS: Adults who were Hispanic, were Black, and/or had lower SES were less likely to use e-cigarettes to quit cigarettes. Findings provide preliminary evidence that differences in harm perceptions may contribute to disparities in e-cigarette transitions.
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Fumar Cigarros , Sistemas Eletrônicos de Liberação de Nicotina , Produtos do Tabaco , Adulto , Humanos , Etnicidade , Hispânico ou Latino , Negro ou Afro-Americano , Brancos , Estados UnidosRESUMO
BACKGROUND: During the COVID-19 pandemic, the high death toll from COVID-19 was accompanied by a rise in mortality from other causes of death. The objective of this study was to identify the relationship between mortality from COVID-19 and changes in mortality from specific causes of death by exploiting spatial variation in these relationships across US states. METHODS: We use cause-specific mortality data from CDC Wonder and population estimates from the US Census Bureau to examine relationships at the state level between mortality from COVID-19 and changes in mortality from other causes of death. We calculate age-standardized death rates (ASDR) for three age groups, nine underlying causes of death, and all 50 states and the District of Columbia between the first full year of the pandemic (March 2020-February 2021) and the year prior (March 2019-February 2020). We then estimate the relationship between changes in cause-specific ASDR and COVID-19 ASDR using linear regression analysis weighted by the size of the state's population. RESULTS: We estimate that causes of death other than COVID-19 represent 19.6% of the total mortality burden associated with COVID-19 during the first year of the COVID-19 pandemic. At ages 25+, circulatory disease accounted for 51.3% of this burden while dementia (16.4%), other respiratory diseases (12.4%), influenza/pneumonia (8.7%) and diabetes (8.6%) also contribute. In contrast, there was an inverse association across states between COVID-19 death rates and changes in death rates from cancer. We found no state-level association between COVID-19 mortality and rising mortality from external causes. CONCLUSIONS: States with unusually high death rates from COVID-19 experienced an even larger mortality burden than implied by those rates alone. Circulatory disease served as the most important route through which COVID-19 mortality affected death rates from other causes of death. Dementia and other respiratory diseases made the second and third largest contributions. In contrast, mortality from neoplasms tended to decline in states with the highest death rates from COVID-19. Such information may help to inform state-level responses aimed at easing the full mortality burden of the COVID-19 pandemic.
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COVID-19 , Doenças Cardiovasculares , Demência , Humanos , Adulto , Pandemias , CausalidadeRESUMO
The present study aimed to examine short- and long-term weight change in a nationally representative sample of US adults who reportedly underwent bariatric surgery. Individuals aged 20-64 at survey from the US National Health and Nutrition Examination Survey 2015-2018 were included in the analyses (n = 6776). The primary comparison groups include 62 participants who underwent bariatric surgery, 1531 eligible but did not receive surgery, and 5183 not eligible for bariatric surgery. After adjusting for demographic characteristics and comorbidity, adults who reported receiving bariatric surgery were 5.0 times (4.0-6.0) more likely to achieve at least 20% weight loss from maximum weight relative to those who were eligible but reported no surgery. The likelihood appeared to be higher when surgery was performed within 10 years (short-term, PR 5.5, 95% CI: 4.0, 7.0) relative to surgeries that were performed for 10 or more years (long-term, PR 3.6, 95% CI: 2.0, 5.3). In this nationally representative sample of US adults, respondents who received bariatric surgery achieved substantial and significant weight loss compared with those who were eligible and did not receive bariatric surgery. Weight loss appeared to be most apparent in the short term and persisted over the long term.
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Cirurgia Bariátrica , Obesidade Mórbida , Adulto , Humanos , Inquéritos Nutricionais , Comorbidade , Inquéritos e Questionários , Redução de Peso , Obesidade Mórbida/cirurgiaRESUMO
INTRODUCTION: E-cigarette use is associated with pulmonary inflammation, functional respiratory changes, and chronic lung disease. Most population-level E-cigarette research has utilized point-in-time measures of E-cigarette exposures, which may not generalize to adults who transition between cigarettes and E-cigarettes. METHODS: Data obtained from the Population Assessment of Tobacco and Health study were collected from 2013 to 2019 and analyzed in 2022. Three observations were created per respondent, with exposure intervals assessed over Waves 1-2, 2-3, and 3-4. Each wave of the exposure interval was classified as nonuse, exclusive E-cigarette use, exclusive smoking, or dual use, producing 16 possible cigaretteâE-cigarette transitions. The association between transitions and both dry nighttime cough and wheeze symptom development during follow-up were assessed using mixed-effects Poisson models. RESULTS: Among 33,231 observations from 13,528 unique participants, transitioning from nonuse to exclusive E-cigarette use was associated with 1.62 times higher incidence rate of wheeze (incident rate ratio=1.62; 95% CI=1.12, 2.34) than persistent nonuse. There was no change in reported dry nighttime cough (incident rate ratio=0.84; 95% CI=0.52, 1.35) or wheeze (incident rate ratio=0.87; 95% CI=0.52, 1.46) in individuals who switched from cigarettes to E-cigarettes, whereas transitioning from dual use to E-cigarette use was associated with large reductions in both symptoms (incident rate ratio=0.58; 95% CI=0.39, 0.87 and incident rate ratio=0.36; 95% CI=0.20, 0.63, respectively). CONCLUSIONS: E-cigarette initiation among nonusers is associated with increased respiratory morbidity. Further research should assess the risks and benefits of E-cigaretteâassisted cigarette cessation given the reduction in symptom development rates among dual use to E-cigarette switchers.
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Sistemas Eletrônicos de Liberação de Nicotina , Produtos do Tabaco , Vaping , Adulto , Humanos , Tosse/epidemiologia , Tosse/etiologia , Fumar/efeitos adversos , Fumar/epidemiologia , Vaping/efeitos adversos , Vaping/epidemiologiaRESUMO
OBJECTIVES: To measure the impact of lost-time occupational injuries on all-cause mortality in Washington State and, using the same data elements and study design, to determine whether the estimated impact was similar to previous estimates for New Mexico. METHODS: We linked injuries in the Washington workers' compensation system with Social Security Administration data on earnings and mortality. We estimated Cox survival models of mortality for women and men with lost-time compared with medical-only injuries, adjusting for age, pre-injury earnings and industry. We used quantitative bias analysis to account for confounding by pre-injury smoking and obesity. RESULTS: The estimated mortality HR was 1.24 for women (95% CI 1.21 to 1.28) and 1.22 for men (95% CI 1.20 to 1.24). After adjusting for unmeasured pre-injury smoking and obesity, the estimated HR for women was 1.10, 95% simulation interval (SI) 1.00 to 1.21; for men, it was 1.15, 95% SI 1.04 to 1.27. CONCLUSIONS: All-cause mortality for Washington workers with lost-time injuries was higher than for those with medical-only injuries. Estimated HRs for Washington were consistent with those previously estimated for New Mexico, a less populous state with lower median wages and a different workers' compensation insurance mechanism. This suggests that the relationship between workplace injury and long-term mortality may be generalisable to other US states. These findings support greater efforts to enhance safety and to investigate factors that improve postinjury employment opportunities and long-term health. This association should be examined in additional locations, with different study conditions, or using additional data on pre-injury risk factors.
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Traumatismos Ocupacionais , Masculino , Feminino , Humanos , Indenização aos Trabalhadores , Local de Trabalho , Renda , Washington/epidemiologia , ObesidadeRESUMO
Detailed description of the prevalence and sources of e-cigarettes among youth is needed to inform effective regulatory policies. We used the Youth Risk Behavior Surveillance System data (2015-2019) to assess trends in current (past-30-day-use) and frequent (≥10 days in past-30-days) e-cigarette use among United States high schoolers before the COVID-19 pandemic. First, we assessed trends overall and then stratified by participants' sociodemographic characteristics, use of other tobacco products, and experiences of psychosocial stress. We also evaluated past year quit attempts and the changing sources of e-cigarettes. Our sample size was 41,021 (15,356-2015; 12,873-2017; 12,792-2019). The prevalence of current e-cigarette use increased from 24.0% (95%CI:21.9%-26.3%) in 2015 to 32.7% (30.4%-35.1%) in 2019. The proportion of current users who reported frequent use also increased significantly from 22.6% (20.4%-24.8%) to 45.4% (42.7%-48.2%). Thus, an increasing proportion of US high school students who use e-cigarettes reported frequent use, indicating greater nicotine dependence. The increase in current and frequent e-cigarette use was more pronounced in youth who reported other substance use and psychosocial stressors such as bullying. Between 2017 and 2019, there was a decline in the proportion of youth who bought e-cigarettes online (6.9% to 3.2%) or from convenience stores (22.0% to 16.6%). Conversely, there was an increase in the proportion who borrowed (34.5% to 40.1%) or purchased e-cigarettes through other people (10.7% to 18.0%), indicating that most youth are evading age-related restrictions by obtaining e-cigarettes from other people. Finally, a considerable proportion of youth tobacco users are making quit attempts; 47.6% (45.1%-50.1%) in 2019.
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AIMS: To estimate the association of longitudinal patterns of e-cigarette use with cigarette smoking abstinence, after accounting for time-dependent confounding and selection bias. DESIGN: Secondary analysis of longitudinal national cohort data. Using marginal structural models and four waves of the population assessment of tobacco and health (wave 1, 2013-14; wave 2, 2014-15; wave 3, 2015-16; wave 4, 2016-18), we estimated the association of vaping frequency across waves 2 and 3 with 12-month sustained cigarette smoking abstinence at wave 4, adjusting for time-dependent confounders at waves 1 and 2 and selection bias due to drop-out with inverse probability of treatment and censoring weights. SETTING: United States. PARTICIPANTS/CASES: A total of 5699 adults (18+ years) who smoked cigarettes and did not vape at wave 1. MEASUREMENTS: The exposure was vaping frequency at waves 2 and 3 (non-use, non-daily use, daily use), representing nine possible combinations of vaping frequency across two waves. Non-use at both waves was the exposure reference group. The primary outcome was sustained 12-month cigarette smoking abstinence at wave 4. FINDINGS: Among 5699 adults who smoked cigarettes at wave 1, a total of 560 (9.8%) reported smoking abstinence at wave 4. Compared with nonuse at both waves, daily vaping at both waves [risk ratio (RR) = 3.82, 95% confidence interval (CI) = 2.59-5.64] and non-use at wave 2 followed by daily vaping at wave 3 (RR = 2.50, 95% CI = 1.66-3.77) were positively associated with smoking abstinence; non-daily vaping at both waves was inversely associated with smoking abstinence (RR = 0.28, 95% CI = 0.11-0.75). Results persisted after accounting for misclassification of e-cigarette use and cigarette smoking abstinence and after restricting to participants with plans to quit smoking. CONCLUSIONS: In a US cohort of adult smokers, longitudinal patterns of vaping frequency appear to predict smoking abstinence, even after accounting for several sources of systematic error. Consistent daily vaping is associated with increased chances of cigarette smoking abstinence, while consistent non-daily vaping is associated with decreased chances of smoking abstinence.
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Fumar Cigarros , Sistemas Eletrônicos de Liberação de Nicotina , Abandono do Hábito de Fumar , Produtos do Tabaco , Vaping , Adulto , Humanos , Estados Unidos , Vaping/epidemiologia , Fumar Cigarros/epidemiologia , Fumantes , Nicotiana , Abandono do Hábito de Fumar/métodosRESUMO
INTRODUCTION: In observational studies, vaping daily is positively associated with cigarette smoking abstinence, while non-daily vaping is associated with less smoking abstinence (versus no e-cigarette use). It remains unknown whether cigarette smokers who vape daily have different motivations for using e-cigarettes than those who vape non-daily. METHODS: Using latent class analysis and 10 self-reported reasons for vaping, we identified sub-groups of participants based on vaping motivations among 1544 adult (≥18 y) dual users of e-cigarettes and cigarettes at wave 4 of the Population Assessment of Tobacco and Health (2016-2018). We examined the association of motivation sub-groups with vaping frequency at wave 4, and subsequent cigarette smoking abstinence at wave 5 (2018-2019). Additional analyses examined the association of vaping frequency with smoking abstinence before and after adjustment for motivation sub-groups. RESULTS: Four distinct sub-groups of e-cigarette users emerged, including 54 % of participants who were "Vaping Enthusiasts", 20 % who vaped for "Convenience and Social Acceptability", 10 % classified as "Experimenters", and 16 % who vaped for "Quitting Smoking and Harm Reduction." The Convenience and Social Acceptability sub-group were less likely than "Vaping Enthusiasts" (AOR=0.29, 95 %CI[0.20-0.42]) and "Quitting Smoking and Harm Reduction" (AOR=0.41, 95 %CI[0.24-0.71]) classes to vape daily (versus non-daily). Sub-groups were not associated with smoking abstinence after one year. Adjustment for motivation sub-groups did not attenuate a positive association of daily vaping with smoking abstinence. CONCLUSIONS: Cigarette smokers who vaped for convenience and social acceptability were less frequent e-cigarette users than those with other vaping motivations. Vaping motivations were not associated with subsequent smoking abstinence.
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Fumar Cigarros , Sistemas Eletrônicos de Liberação de Nicotina , Abandono do Hábito de Fumar , Produtos do Tabaco , Vaping , Adulto , Humanos , Motivação , Nicotiana , Estados Unidos/epidemiologia , Vaping/epidemiologiaRESUMO
Importance: Updated data on the patterns of e-cigarette use among adults in the US are needed. Objective: To examine recent patterns in current and daily e-cigarette use among US adults. Design, Setting, and Participants: This repeated cross-sectional study used data from the 2017, 2018, and 2020 Behavioral Risk Factor Surveillance System, a nationally representative state-based survey of noninstitutionalized US adults. A total of 994 307 adults 18 years and older who were living in states and territories that provided data on e-cigarette use in 2017 (53 states and territories), 2018 (36 states and Guam), and 2020 (42 states and Guam) were included. Main Outcomes and Measures: The weighted prevalence of current (past 30 days) and daily e-cigarette use was estimated for each year, and changes in prevalence from 2017 to 2020 were assessed, first overall and then stratified by participant characteristics, including state or territory of residence. Results: Among 994 307 adults from states with data on e-cigarette use, 429â¯370 individuals (weighted 51.3% female) were participants in the 2017 survey, 280â¯184 (weighted 52.1% female) were participants in the 2018 survey, and 284â¯753 (weighted 52.1% female) were participants in the 2020 survey. The weighted proportions of young adults aged 18 to 24 years were 12.6% in 2017, 11.8% in 2018, and 11.9% in 2020. Across all 3 years, 17 035 participants (weighted, 1.0%) were American Indian or Alaska Native, 22 313 (weighted, 4.6%) were Asian, 75 780 (weighted, 12.2%) were Black, 72 190 (weighted, 15.1%) were Hispanic, 4817 (weighted, 0.2%) were Native Hawaiian, 757 140 (weighted, 65.1%) were White, 20 332 (weighted, 1.3%) were multiracial, and 6245 (weighted, 0.5%) were of other races and/or ethnicities. The prevalence of current e-cigarette use was 4.4% (95% CI, 4.3%-4.5%) in 2017, which increased to 5.5% (95% CI, 5.4%-5.7%) in 2018 and decreased slightly to 5.1% (95% CI, 4.9%-5.3%) in 2020. The recent decrease, though modest, was observed mainly among young adults aged 18 to 20 years (from 18.9% [95% CI, 17.2%-20.7%] to 15.6% [95% CI, 14.1%-17.1%]; P = .004). However, the prevalence of daily e-cigarette use increased consistently from 1.5% (95% CI, 1.4%-1.6%) in 2017 to 2.1% (95% CI, 2.0%-2.2%) in 2018 and 2.3% (95% CI, 2.2%-2.4%) in 2020. Among young adults aged 21 to 24 years, there was a slight, albeit insignificant, increase in the prevalence of current e-cigarette use (from 13.5% [95% CI, 12.3%-14.7%] to 14.5% [95% CI, 13.2%-15.9%]; P = .28) but a significant increase in the prevalence of daily e-cigarette use (from 4.4% [95% CI, 3.8%-5.1%] to 6.6% [95% CI, 5.6%-7.6%]; P < .001) between 2018 and 2020. State-level patterns in the prevalence of current e-cigarette use were heterogeneous, with states like Massachusetts (from 5.6% [95% CI, 4.8%-6.5%] to 4.1% [95% CI, 3.1%-5.3%]; P = .03) and New York (from 5.4% [95% CI, 4.9%-5.9%] to 4.1% [95% CI, 3.5%-4.7%]; P = .001) recording significant decreases between 2018 and 2020. In contrast, Guam (from 5.9% [95% CI, 4.5%-7.9%] to 11.4% [95% CI, 8.7%-14.8%]; P = .002) and Utah (from 6.1% [95% CI, 5.5%-6.7%] to 7.2% [95% CI, 6.5%-8.0%]; P = .02) recorded significant increases in current e-cigarette use over the same period. Conclusions and Relevance: In this study, a slight decrease in the prevalence of current e-cigarette use was found between 2018 and 2020; this decrease was mainly observed among young adults aged 18 to 20 years. In contrast, daily e-cigarette use consistently increased, particularly among young adults aged 21 to 24 years. This increase in daily use suggests greater nicotine dependence among those who use e-cigarettes, warranting continued surveillance.
Assuntos
Sistemas Eletrônicos de Liberação de Nicotina , Tabagismo , Vaping , Sistema de Vigilância de Fator de Risco Comportamental , Estudos Transversais , Feminino , Humanos , Masculino , Vaping/epidemiologia , Adulto JovemRESUMO
BACKGROUND: Youth e-cigarette use is associated with the initiation of combustible cigarette smoking, but prior studies have rarely accounted for time-varying measures of e-cigarette exposure or time-dependent confounding of e-cigarette use and smoking initiation. METHODS: Using five waves of the Population Assessment of Tobacco and Health (2013-2019), we estimated marginal structural models with inverse probability of treatment and censoring weights to examine the association between time-varying e-cigarette initiation and subsequent cigarette smoking initiation among e-cigarette- and cigarette-naïve youth (12-17 years) at baseline. Time-dependent confounders used as predictors in inverse probability weights included tobacco-related attitudes or beliefs, mental health symptoms, substance use, and tobacco-marketing exposure. RESULTS: Among 9,584 youth at baseline, those who initiated e-cigarettes were 2.4 times as likely to subsequently initiate cigarette smoking as youth who did not initiate e-cigarettes (risk ratio = 2.4, 95% confidence interval [CI] = 2.1, 2.7), after accounting for time-dependent confounding and selection bias. Among youth who initiated e-cigarettes, more frequent vaping was associated with greater risk of smoking initiation (risk ratio ≥3 days/month = 1.8, 95% CI = 1.4, 2.2; 1-2 days/month = 1.2; 95% CI = 0.93, 1.6 vs. 0 days/month). Weighted marginal structural model estimates were moderately attenuated compared with unweighted estimates adjusted for baseline-only confounders. At the US population level, we estimated over half a million youth initiated cigarette smoking because of prior e-cigarette use over follow-up. CONCLUSIONS: The association between youth vaping and combustible cigarette smoking persisted after accounting for time-dependent confounding. We estimate that e-cigarette use accounts for a considerable share of cigarette initiation among US youth. See video abstract at, http://links.lww.com/EDE/B937.