BACKGROUND:Tobacco use is closely linked to social and health inequalities, including economic vulnerability, morbidity, and premature death. Young adults with disabilities experience significant social and material hardships, which may be exacerbated by tobacco use. Limited research exists on smoking and e-cigarette use in this population. This study examines the prevalence of disability among young adults in Ireland, compares smoking and e-cigarette use between those with and without disabilities, identifies protective and risk factors, explores shared risk factors, and evaluates disability as an independent risk factor for smoking and e-cigarette use. METHODS:We analysed weighted data from 4,729 20-year-olds in the Growing Up in Ireland Cohort '98 study who were present in Waves 1 (2008), 3 (2016), and 4 (2019). Current smoking, e-cigarette use, disability (excluding mental ill-health) and all other variables were assessed at Wave 4, while peer smoking data were drawn from Wave 3. Analyses were conducted using SPSS version 27. RESULTS:18.1% of participants reported a disability, which was associated with significantly higher smoking (41.8% vs. 36.7%) and e-cigarette use (16.1% vs. 12.9%). Protective factors against both behaviours included being female (OR 0.87 for smoking, OR 0.57 for e-cigarettes), later smoking initiation (OR 0.35, OR 0.62), living in two-parent families (OR 0.83, OR 0.70), and physical activity (smoking only). Risk factors included having peers who smoked (OR 3.67 for smoking; OR 2.36 for e-cigarette use) and caregivers who smoked (OR 1.48, OR 1.48), being employed at age 20 (OR 1.58, OR 1.48), and social media engagement (smoking only). Young adults with disabilities were significantly more likely to experience risk factors (e.g., earlier smoking initiation, caregivers who smoked, one-parent families, employment) but were less likely to have peers who smoked or engage with social media. Disability was independently associated with a higher likelihood of smoking (by 54%) and e-cigarette use (by 36%) after adjusting for protective and risk factors. CONCLUSION:Higher smoking and e-cigarette use in 20-year-olds with disabilities adds further inequality to their lives. Increased awareness, targeted surveys and focused prevention and therapeutic interventions are required to reduce inequalities in this population and hasten the tobacco endgame.

The design of e-cigarettes (e-cigs) is constantly evolving and the latest models can aerosolize using high-power sub-ohm resistance and hence may produce specific particle concentrations. The aim of this study was to evaluate the aerosol characteristics generated by two different types of electronic cigarette in real-world conditions, such as a sitting room or a small office, in number of particles (particles/cm3). We compared the real time and time-integrated measurements of the aerosol generated by the e-cigarette types Just Fog and JUUL. Real time (10s average) number of particles (particles/cm3) in 8 different aerodynamic sizes was measured using an optical particle counter (OPC) model Profiler 212-2. Tests were conducted with and without a Heating, Ventilating Air Conditioning System (HVACS) in operation, in order to evaluate the efficiency of air filtration. During the vaping sessions the OPC recorded quite significant increases in number of particles/cm3. The JUUL e-cig produced significantly lower emissions than Just Fog with and without the HVACS in operation. The study demonstrates the rapid volatility or change from liquid or semi-liquid to gaseous status of the e-cig aerosols, with half-life in the order of a few seconds (min. 4.6, max 23.9), even without the HVACS in operation. The e-cig aerosol generated by the JUUL proved significantly lower than that generated by the Just Fog, but this reduction may not be sufficient to eliminate or consistently reduce the health risk for vulnerable non e-cig users exposed to it.

Background: Ireland’s Smoking Ban reduced health inequalities known to be associated with smoking but some groups may not have benefitted. Mental ill-health and smoking are known to be associated with health inequalities. Whether similar patterns exist for e-cigarette use is less clear, as few data exist. Objectives: To examine: (1) self-reported doctor-diagnosed mental ill-health in Irish 20-year-olds; (2) smoking, e-cigarette, and dual use in those with and without mental ill-health; and (3) protective and risk factors for smoking and e-cigarette use in these groups. Methods: We use cross-sectional data from 20 year-olds in Wave 4 of Growing Up in Ireland Child Cohort. They were asked to self-report mental ill-health which had been diagnosed by a clinician, and their smoking and e-cigarette use. All analyses were performed using SPSS v27. Results: 19.4% (n = 1008) of the total sample (n = 4729) reported a mental ill-health diagnosis. Comparing those with and without, those with mental ill-health had significantly higher prevalence of current smoking (47%, n = 419 vs 36%, n = 1361; OR 1.57, CI: 1.36, 1.82), e-cigarette use (17%, n = 152 vs 13%, n = 485; OR 1.40, CI:1.15, 1.70), and dual use (12%, n = 109 vs 9%, n = 328; OR 1.46, CI:1.16, 1.84). Risk factors for smoking and e-cigarette use were, earlier smoking initiation, peers or primary caregivers who smoked, being in paid employment, one-parent family background, and social media use. Being female was protective. Most risk factors were significantly higher in young adults with mental ill-health but, after adjusting for these variables, respondents with mental ill-health still have significantly higher adjusted higher odds of smoking (aOR 1.28, CI:1.05, 1.56). Conclusions: Inequalities in smoking and e-cigarette use in young adults with mental ill-health are evident 20 years after Ireland’s National Smoking Ban. Despite extensive Tobacco Control interventions in the past 20 years, there is still need in Ireland for new targeted interventions to reduce health inequalities for left-behind young smokers with mental ill-health.

INTRODUCTION:Tobacco use is a major threat to health globally. A number of countries have adopted "endgame goals" to minimize smoking prevalence. The INSPIRED project aims to describe and compare the experiences of the first six countries to adopt an endgame goal. AIMS AND METHODS:Data were collected on the initial experiences of endgame goals in Canada, Finland, Ireland, New Zealand (Aotearoa), Scotland, and Sweden up to 2018. Information was collated on the nature of the endgame goals, associated interventions and strategies, potential enablers and barriers, and perceived advantages and disadvantages. RESULTS:The INSPIRED countries had relatively low smoking prevalences and moderate-to-strong smoke-free policies. Their endgame goals aimed for smoking prevalences of 5% or less. Target dates ranged from 2025 to 2035. Except for New Zealand (Aotearoa), all countries had an action plan to support their goal by 2018. However, none of the plans incorporated specific endgame measures. Lack of progress in reducing inequities was a key concern, despite the consideration of equity in all of the country's goals and/or action plans. Experience with endgame goals was generally positive; however, participants thought additional interventions would be required to equitably meet their endgame goal. CONCLUSIONS:There was variation in the nature and approach to endgame goals. This suggests that countries should consider adopting endgame goals and strategies to suit their social, cultural, and political contexts. The experiences of the INSPIRED countries suggest that further and more significant interventions will be required for the timely and equitable achievement of endgame goals. IMPLICATIONS:By 2018, six countries (Canada, Finland, Ireland, New Zealand (Aotearoa), Scotland, and Sweden) had introduced government-endorsed "endgame goals," to rapidly reduce smoking prevalence to very low levels by a specified date. The nature and implementation of endgame goals were variable. Early experiences with the goals were generally positive, but progress in reducing smoking prevalence was insufficient, particularly for priority groups. This finding suggests more significant interventions ("endgame interventions") and measures to reduce inequities need to be implemented to achieve endgame goals. Variation in the nature and experience of endgame goals demonstrates the importance of designing endgame strategies that suit distinct social, cultural, and political contexts.

INTRODUCTION Allen Carr's (AC) method is a pharmacotherapy-free approach to quit smoking that is delivered through seminars, online courses, or in the form of a book. It has gained popularity, but its effectiveness remains controversial due to a lack of scientific evidence. This systematic review aims to provide an updated overview of the current evidence on the effectiveness of the AC method.METHODS We conducted a systematic literature review of all epidemiological studies evaluating the effectiveness of the AC method for smoking cessation, published in PubMed/MEDLINE and Embase up to March 2023.RESULTS Among 34 original studies identified through the literature search, six met the inclusion criteria. These studies were published between 2006 and 2020, with sample sizes ranging from 92 to 620 participants. Of the six studies, two did not have a comparison group while four, including two randomized control led trials (RCT), had a comparison group. The included studies showed cessation rates for people who attended the seminars from 19% to 51%. An observational study found an odds ratio (OR) of abstinence for those attending AC single-session seminars of 6.52 (95% confidence interval, CI: 3.10-13.72) compared with controls with no treatment. One RCT found higher quit rates for AC single-session seminars compared with the online Irish National service (OR=2.26; 95% CI: 1.22-4.21). Another RCT reported no significant difference between AC single-session seminars and a specialist stop smoking service. One single study on patients with head and neck disorders analyzed the effectiveness of reading the AC book, showing no significant results.CONCLUSIONS The AC seminar may be an effective intervention for smoking cessation. This approach deserves further RCTs with large sample sizes to strengthen the evidence. Scant data are available on the effectiveness of reading the AC book.

Drongelen-What is the success rate of trial of labor in monochorionic

BACKGROUND:Smoking is inversely related to people's Physical Activity Level (PAL). As the behavior of friends may affect the choices and behavior of adolescents, having friends with a high PAL may potentially protect against adolescent smoking. This study aims to assess whether adolescents' smoking is associated with the PAL of their friends. METHODS:SILNE-R survey data of 11.918 adolescents from 55 different schools in 7 European cities was used to determine weekly smoking, individual PAL, PAL of friends, school PAL, and smoking of friends. Multilevel, multivariable logistic regression analysis were used to assess the association between the PAL of friends and weekly smoking. Several socio-demographic variables were included as covariates in the analysis. RESULTS:Our results indicated that 10.8% of the respondents was smoking weekly. Weekly smoking was most common among adolescents whose friends had a PAL of 0-42.0 min per day (14.5%). Respondents were significantly more likely to be smoking weekly if their friends were on average 0-42 min vs. 80-180 min physically active (OR 1.27 [95% CI 1.04-1.55]). This association existed independently of the individual PAL of respondents. Stratification for smoking of friends yielded equal results, although the association appeared to be somewhat stronger for those with smoking friends (OR 1.38 [95% CI 1.06-1.82]). CONCLUSION:Adolescents are less likely to smoke weekly if they associate with friends who spend >80 min per day on physical activity. Initiatives aimed at the prevention of smoking among adolescents may benefit from organizing group-based physical activity programs.

We analyse parental smoking and cessation (quitting) associations with teenager e-cigarette, alcohol, tobacco smoking and other drug use, and explore parental smoking as a mechanism for social reproduction. We use data from Waves 1–3 of Growing Up in Ireland (Cohort ’98). Our analytic sample consisted of n = 6,039 participants reporting in all 3 Waves. Data were collected in Waves 1 and 2 when the children were 9 and 13 years old and in Wave 3 at age 17/18 years. Generalized Estimating Equations (GEE) models were used to analyse teenage substance use at Wave 3. Parental smoking was associated with significantly increased risk of all teenage substance use, adjusted odds ratios were aOR2.13 (ever e-cigarette use); aOR1.92 (ever alcohol use); aOR1.88 (current alcohol use); aOR1.90 (ever use of other drugs); aOR2.10 (ever-smoking); and aOR1.91 (current smoking). Primary caregiver smoking cessation (quitting) was associated with a lower risk for teenager current smoking aOR0.62, ever e-cigarette use aOR 0.65 and other drug use aOR 0.57. Primary caregiver smoking behaviour had greater associations than secondary, and age13 exposure more than age 9. Habitus seems to play a role and wealth was protective for teenage smoking. The findings suggest that prevention interventions should target both caregivers and their children.

The association between current smoking and coronavirus disease 2019 (COVID-19) progression remains uncertain. We aim to provide up-to-date evidence of the role of cigarette smoking in COVID-19 hospitalisation, severity and mortality. On 23 February 2022 we conducted an umbrella review and a traditional systematic review via PubMed/Medline and Web of Science. We used random-effects meta -analyses to derive pooled odds ratios of COVID-19 outcomes for smokers in cohorts of severe acute respiratory syndrome coronavirus 2 infected individuals or COVID-19 patients. We followed the Meta -analysis of Observational Studies in Epidemiology reporting guidelines. PROSPERO: CRD42020207003. 320 publications were included. The pooled odds ratio for current versus never or nonsmokers was 1.08 (95% CI 0.98-1.19; 37 studies) for hospitalisation, 1.34 (95% CI 1.22-1.48; 124 studies) for severity and 1.32 (95% CI 1.20-1.45; 119 studies) for mortality. Estimates for former versus never-smokers were 1.16 (95% CI 1.03-1.31; 22 studies), 1.41 (95% CI: 1.25-1.59; 44 studies) and 1.46 (95% CI 1.31-1.62; 44 studies), respectively. Estimates for ever-versus never-smokers were 1.16 (95% CI 1.05-1.27; 33 studies), 1.44 (95% CI 1.31-1.58; 110 studies) and 1.39 (95% CI 1.29-1.50; 109 studies), respectively. We found a 30-50% excess risk of COVID-19 progression for current and former smokers compared with never -smokers. Preventing serious COVID-19 outcomes, including death, seems the newest compelling argument against smoking.