Tobacco Use Insights最新文献

Introduction: Research has documented higher smoking prevalence with unemployment and greater difficulty with gaining re-employment for those who smoke. Using photo elicitation methods, we sought to gain a deeper understanding of the connection between job-seeking and tobacco use.

Methods: Unemployed daily smokers (18 men, 1 woman) were recruited from the San Francisco Employment Development Department (EDD) and provided disposable cameras with 27 exposures and a list of 20 photo prompts related to job-seeking and tobacco. Study staff reviewed the photos with the participants and audio-recorded their narratives. The photos and narratives were coded for themes.

Results: Of 363 photos, the most frequent photo imagery related to transportation (n = 56, 15.4%), work or education (n = 39, 10.7%), and littered cigarettes (n = 39, 10.7%). Narrated themes centered on motivators to quit smoking (255 mentions from 15 participants); people, places, and things associated with smoking (248 mentions, 16 participants); and motivators to secure work (157 mentions, 13 participants). The intersection of smoking and unemployment received 92 mentions from 11 participants, with 60 mentions (8 participants) identifying smoking as a barrier to re-employment.

Conclusions: Both motivators to quit and associated smoking cues were salient in the environments of job-seeking smokers. Struggles with quitting and perceptions that smoking is harming re-employment success suggest the potential for offering tobacco treatment in EDD settings. With permission, the photos and themes have been incorporated into a tobacco treatment intervention for job-seeking smokers.

Background: Electronic cigarette regulations included in the Tobacco Products Directive (TPD), Article 20, implemented in Europe by May 2017, aimed to improve safety for e-cigarette consumers, and prevent uptake among non-smokers, particularly young people. Before implementation, there were significant concerns from consumers, industry, and some in the scientific community about the potential negative impact of the TPD on people using e-cigarettes to remain abstinent from smoking. To date, there is limited evidence on how the TPD has affected consumers. This study aimed to add insight into how consumers perceived and experienced the regulations.

Methods: Qualitative data, collected between March 2018 and March 2019, relating to participant views of the TPD were extracted from 160 interviews/extended surveys of e-cigarette consumers as part of a wider study into e-cigarette use trajectories (ECtra study). Data were thematically analysed.

Results: Awareness of the TPD among consumers was not universal. Participants' smoking behaviour did not appear to be influenced by the legislation. Participants were reassured by manufacturing regulations and requirements for ingredients labels. Participants responded negatively to changes perceived to cause inconvenience and extra plastic waste. The product restrictions prompted some participants to purchase non-compliant products illegally, potentially putting their safety at risk.

Conclusions: E-cigarette regulation should focus on ensuring product safety. Raising awareness of the TPD among consumers and smokers could be beneficial.

Background: Hookah tobacco use is common among young adults. Unlike cigarette smoking, there is limited evidence on mobile (ie, mHealth) interventions to promote cessation.

Objectives: This pilot study tested the preliminary effects of mobile messaging for cessation in young adult hookah smokers.

Methods: Young adults (N = 20) aged 18 to 30 years who smoke hookah at least monthly and have done so at least once in the past 30 days received a 6-week mHealth multimedia messaging (text and images) intervention. Message scheduling (2 days/week × 6 weeks) was based on the literature. Content was developed iteratively by the study team and focused on health harms and addictiveness of hookah. Content was individually tailored by baseline hookah use frequency, risk beliefs, and responses to interactive text messages assessing participants' hookah tobacco use behavior and beliefs to maximize impact. Engagement was assessed during the intervention, and we examined effects on risk perceptions, risk beliefs, and risk appraisals, motivation to quit, and behavior change immediately post-intervention.

Results: Participants responded to 11.5 (SD = 0.69) of 12 text message prompts on average, endorsed high message receptivity (M = 6.1, SD = 0.93, range = 1-7), and reported the messages were helpful (M = 8.5, SD = 1.5, range = 1-10). There were significant (P < .05) increases in risk perceptions (d's = 0.22-0.88), risk appraisals (d = 0.49), risk beliefs (d = 1.11), and motivation to quit (d = 0.97) post-intervention. Half of participants reported reducing frequency of hookah use (20%) or quitting completely (30%) by end of treatment.

Conclusions: These pilot results provide preliminary support for an mHealth messaging intervention about risks of hookah tobacco for promoting cessation. Rigorously examining the efficacy of this promising intervention is warranted.

Introduction: The popularity of e-cigarettes has increased significantly in recent years. E-cigarettes are perceived as less harmful than cigarettes, and both dual-use of cigarette and e-cigarette use is common among adolescents. This study assessed cigarette and e-cigarette risk perception and associations with dual-product use among Canadian adolescents.

Methods: We used data from the 2016-2017 Canadian Student Tobacco, Alcohol, and Drugs Survey. Perceived risks of cigarette and e-cigarette use were classified into 4 categories: "high-risk perception," "high-e-cigarette-risk and low-cigarette-risk perception," "low-e-cigarette-risk and high-cigarette-risk perception," and "low-risk perception." Adjusted odds ratios (aOR) were estimated from multinomial logistic regression.

Results: Of the population, 92% perceived high risk from cigarettes, and 65% from e-cigarettes. Compared to students with low-risk perception, those with high-risk perception of both products had lower odds of dual-use (aOR: 0.21; 95% confidence interval [CI]: 0.15, 0.28), cigarette-only use (aOR: 0.33; 95% CI: 0.25, 0.45), and e-cigarette-only use (aOR: 0.64; 95% CI: 0.51, 0.79) relative to nonusers. Adolescents with high-e-cigarette and low-cigarette-risk perception had higher odds of e-cigarette-only use, relative to nonusers. Those with high-risk perception were more likely to be e-cigarette-only users relative to cigarette-only users.

Conclusion: Results highlight that high perceived risk is associated with lower odds of use. However, those with a high-risk perception of both products had higher odds of e-cigarette use relative to cigarette-only users; as did those with high-e-cigarette and low-cigarette-risk perception, relative to nonusers. Future research should assess ways of communicating the risks of adolescent tobacco use.

Background: Despite prior studies, transitions in smoking patterns are not fully understood. Getting arrested may alter an individual's smoking pattern through processes proscribed by the criminological labeling theory. This study examined how arrest during emerging adulthood altered smoking behavior during subsequent years and whether there were differential effects by race/ethnicity and gender.

Methods: We analyzed 15 waves of data from the National Longitudinal Survey of Youth 1997. Multinomial logistic regressions were performed using Stata software version 14.

Results: For both genders, arrested black men and women had the most distinct smoking transitions (both increases and decreases) as compared with their non-arrested counterparts. Among men, particularly black males, arrest in early adulthood was associated with the men transitioning to both increased and decreased smoking. Patterns in smoking transitions for women were less clear, suggesting that women's smoking may be influenced by factors not in the models. Women had a low probability of starting to smoke or increasing smoking if they were never arrested between 18 and 21 years of age.

Conclusions: The results for transitioning into increased smoking offer some support for labeling theory processes. Other findings suggest that arrest may lead to some men reducing or quitting smoking. Early adulthood arrest may serve to "shock the system" and contribute to males altering their prior smoking behavior.

Implications: Tobacco use over the life course, particularly across different racial and ethnic groups, remains understudied. This study contributes to the literature using a nationally representative sample to examine the effect of getting arrested in emerging adulthood on cigarette use during subsequent years. In conducting the study, investigators combined theories and methodological approaches from 2 complementary disciplines: public health and criminal justice. Because criminal justice policymakers tend to focus on issues like ex-offender unemployment, public health officials can provide guidance regarding the effect of justice system involvement on smoking, particularly given the adverse health outcomes of using cigarettes.

Background: A significant proportion of the Algerian population uses tobacco products and is at risk of developing tobacco-associated cancers.

Aims: This case-control study reports on the association between tobacco use and the occurrence of upper aerodigestive tract (UADT) cancers in Batna, Algeria.

Methods: Incident primary UADT cancer cases in residents of Batna in 2008-2011 were identified using the regional tumor registry. One hospital and 1 population control were matched to each case by sex, year of birth, and residence. Information on tobacco use was collected, and odds ratios (ORs) were obtained using conditional logistic regression also after sex stratification.

Results: The study included 192 cases (80%) of the 241 primary UADT cancer cases identified and 384 controls. Males represented 76.6% of cancer cases. Cancers of the nasopharynx (48%) and the larynx (26%) were the most common types. Ever use of smokeless tobacco (ST) (OR = 1.0; 95% confidence interval [CI]: 0.6-1.5) or current ST use (OR = 1.1; 95% CI: 0.6-1.7) was not associated with overall risk of UADT cancers. Associations with cancers of the nasopharynx (OR = 1.5; 95% CI: 0.5-4.6) and oral cavity/oropharynx (OR = 3.0; 95% CI: 0.8-11.8) were found when comparing use of ST only to no consumption of any tobacco. Cigarette smoking was associated with an increase in the overall risk of UADT cancers, with a 3-fold increase in the risk of laryngeal cancer when comparing smoking only to no consumption of any tobacco (OR = 3.3; 95% CI: 1.0-11.5). Associations for smokers who also consumed ST differed by cancer site.

Conclusion: In this study from Algeria dominated by male cases and by cancer in the nasopharynx, cigarette smoking but not ST was associated with UADT cancer. Analyses by anatomical site and using as reference never use of any type of tobacco suggested few associations with ST but of lower precision.

Background: Studies have demonstrated the effectiveness of text message-based prevention programs on smoking cessation, including our recently published TEXTME randomised controlled trial. However, little is known about the predictors of smoking cessation in this context and if other clinically important factors interact with the program to lead to quitting. Hence, the objective of this study was to first assess the predictors of smoking cessation in TEXTME and then determine if the effect of texting on quitting was modified by interactions with important clinical variables. This will allow us to better understand how text messaging works and thus help optimise future text-message based prevention programs.

Methods: This sub-analysis used data collected as part of the TEXTME trial which recruited 710 participants (377 current smokers at baseline) between September 2011 and November 2013 from a large tertiary hospital in Sydney, Australia. Smokers at baseline were analysed at 6 months and grouped into those who quit and those who did not. Univariate analyses were performed to determine associations between the main outcome and clinically important baseline factors selected a priori. A multiple binominal logistic regression analysis was conducted to develop a predictive model for the dependent variable smoking cessation. A test of interaction between the intervention group and baseline variables selected a priori with the outcome smoking cessation was performed.

Results: Univariate analysis identified receiving text-messages, age, and mean number of cigarettes smoked each day as being associated with quitting smoking. After adjusting for age, receiving the text-messaging program (OR 2.34; 95%CI 1.43-3.86; p<0.01) and mean number of cigarettes smoked per day (OR 1.02; 95%CI 1.00-1.04; p=0.03) were independent predictors for smoking cessation. LDL-C showed a significant interaction effect with the intervention (High LDL*Intervention OR 3.77 (95%CI 2.05-6.94); Low LDL*Intervention OR 1.42 (95%CI 0.77-2.60); P=0.03).

Conclusions: Smoking quantity at baseline is independently associated with smoking cessation and higher LDL-C may interact with the intervention to result in quitting smoking. Those who have a higher baseline risk maybe more motivated towards beneficial lifestyle change including quitting smoking, and thus more likely to respond to mHealth smoking cessation programs. The effect of text-messages on smoking cessation was independent of age, gender, psychosocial parameters, education, and baseline control of risk factors in a secondary prevention cohort.

Objectives: Smoking cessation interventions with sex considerations have been found to effectively increase cessation rates. However, evidence is limited and weak. This study examined sex differences in the use of smoking cessation services or resources among Ontario adults.

Methods: Data are from the Smokers' Panel, an ongoing online survey of Ontario adult smokers and recent quitters. The analysis included 1009 male and 1765 female participants. Bivariate analysis was used to examine differences in sociodemographic characteristics and smoking-related variables by use of cessation services/resources. Logistic regression was then used to identify sociodemographic characteristics and smoking-related variables associated with the use of cessation services/resources.

Results: The analysis shows that there were significant sex differences in the use of individual interventions. Female participants were more likely to use nicotine patch (63% vs 58%; adjusted odds ratio, AOR: 1.39, 95% confidence interval [CI]: 1.16-1.67), varenicline (29% vs 24%; AOR: 1.37, 95% CI: 1.13-1.66), Smokers' Helpline phone (14% vs 10%; AOR: 1.39, 95% CI: 1.07-1.79), Smokers' Helpline online (27% vs 21%; AOR 1.43, 95% CI: 1.18-1.74), self-help materials (23% vs 16%; AOR: 1.81 95% CI: 1.46-2.26), and alternative methods (23% vs 19%; AOR: 1.40, 95% CI: 1.14-1.73) compared with male participants, after adjusting for covariates.

Conclusion: Consistent with other findings, the study shows sex differences in the use of smoking cessation services or resources among adult smokers. Women are more likely to use recommended cessation resources such as nicotine patch, varenicline, and Smokers' Helpline than men. Health professionals should use this increased willingness to help female smokers quit. However, men may be underserved and more men-specific interventions need to be developed and evaluated.

Background: Tobacco use is a global pandemic, affecting an estimated 1.2 billion people and resulting in substantial health burdens and associated costs.

Objectives: The aim of this study was to estimate the efficacy of several treatments for smoking cessation in a real-life setting and to evaluate predictors of smoking abstinence.

Methods: This research was designed with a sample of 593 cases recorded over the period between 2015 and 2016. Six treatment groups were included: (1) bupropion and motivational interviewing (MI); (2) bupropion, nicotine replacement therapy (NRT), and MI; (3) NRT and MI; (4) varenicline and MI; (5) personal vaporizer electronic cigarette and MI; and (6) electronic cigarette, cigarette like "cigalike," and MI.

Results: Results support the efficacy of all treatment groups when used in a real-life setting. The predictors of smoking abstinence were sex, partner smoking status, previous quit attempts, daily consumption, self-efficacy, and level of nicotine dependence.

Conclusions: The use of different therapeutic strategies in clinical practice, including pharmacotherapy and nonstandard electronic nicotine delivery systems, such as an electronic cigarette, ensures a greater chance of cessation success and the possibility of tailoring interventions according to patients' resources.