Trends In Smoking Cessation Research Articles

Demographic factors associated with smoking cessation during pregnancy in New South Wales, Australia, 2000-2011.

BackgroundSmoking during pregnancy increases the risk of adverse health outcomes for both the mother and the child. Rates of smoking during pregnancy, and rates of smoking cessation during pregnancy, vary between demographic groups. This study describes demographic factors associated with smoking cessation during pregnancy in New South Wales, Australia, and describes trends in smoking cessation in demographic subgroups over the period 2000 – 2011.MethodsData were obtained from the New South Wales Perinatal Data Collection, a population-based surveillance system covering all births in New South Wales. Multivariate logistic regression was used to explore associations between smoking cessation during pregnancy and demographic factors.ResultsBetween 2000 and 2011, rates of smoking cessation in pregnancy increased from 4.0% to 25.2%. Demographic characteristics associated with lower rates of smoking cessation during pregnancy included being a teenage mother, being an Aboriginal person, and having a higher number of previous pregnancies.ConclusionsBetween 2000 and 2011, rates of smoking cessation during pregnancy increased dramatically across all demographic groups. However, specific demographic groups remain significantly less likely to quit smoking, suggesting a need for targeted efforts to promote smoking cessation in these groups.

The effect of tobacco control policy on smoking cessation in relation to gender, age and education in Lithuania, 1994-2010.

BackgroundThis study aimed to evaluate the association between tobacco control policies and trends in smoking cessation according to gender, age and educational level in Lithuania in 1994–2010.MethodsThe data were obtained from nine cross-sectional postal surveys conducted biennially within the framework of Finbalt Health Monitor project during 1994–2010. Each survey was based on a nationally representative random sample drawn from the National population register. The sample consisted of 3000 citizens aged 20–64 in 1994–2008 surveys and 4000 in the 2010 survey. In total, 17161 individuals participated in all surveys. The development of tobacco control policy in Lithuania was assessed using the Tobacco Control Scale (TCS). The association of the TCS scores with short-term and long-term quitting according to gender, age and education was examined using logistic regression analysis with control for secular trends.ResultsOver the last two decades, a large improvement in the development of tobacco control policy has been achieved in Lithuania. At the same time, this progress was associated with the increase in smoking cessation. A significant increase in both short-term and long-term quit ratios was found among people aged 20–44. An increase by 10 points on the TCS was associated with 17% increase in the odds of short-term quitting and with 15% increase in the odds of long-term quitting. The association between tobacco control policies and long-term quitting was stronger among younger than older people. No differential effect of tobacco control policies on smoking cessation was found in relation to gender and educational level.ConclusionsThe improvement in Lithuanian tobacco control policies was associated with an increase in smoking cessation in long-term perspective. These policies have not only benefitted highly educated groups, but lower educated groups as well. Nonetheless, further development of comprehensive tobacco control policies is needed in order to decrease social inequalities in smoking cessation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-1525-8) contains supplementary material, which is available to authorized users.

The Association Between Tobacco Control Policy and Educational Inequalities in Smoking Cessation in the Netherlands from 1988 Through 2011.

Tobacco control policies seemed to have failed to reduce socioeconomic inequalities in smoking in the past. It has been argued that a comprehensive mix of policies is needed. Our aim was to assess whether tobacco control policy development in the Netherlands between 1988 and 2011 was associated with educational inequalities in smoking cessation and cigarette consumption. Data were derived from the cross-sectional Dutch Continuous Survey of Smoking Habits, with a study sample of 259,140 respondents from 1988 through 2011. Outcomes were the quit ratio and mean number of cigarettes smoked per day. The determinant was the Tobacco Control Scale (TCS). We used multilevel logistic regression modeling, with years, quarters, and individuals as levels, and controlled for sex, age, and time. A significant association between the TCS and smoking cessation was found in 2001-2011, but not in 1988-2000. Associations for low- and high-education groups were similar (OR = 1.23; 95% CI = 1.12-1.34 and OR = 1.17; 95% CI = 1.03-1.32 respectively). The TCS was not significantly associated with the number of cigarettes smoked per day for either the low- or high-education groups (B = -0.09; 95% CI = -0.46-0.27 and B = -0.59; 95% CI = -1.24-0.06 respectively). Strong tobacco control policies introduced in the Netherlands after 2000 were positively associated with national trends in smoking cessation, whereas weaker policies introduced gradually before 2000 were not. However, these measures do not seem to have either widened or narrowed educational inequalities in smoking cessation rates-both groups benefitted about equally.

Trends in smoking cessation: a Markov model approach

Intervention trials such as studies on smoking cessation may observe multiple, discrete outcomes over time. When the outcome is binary, participant observations may alternate between two states over the course of the study. The generalized estimating equation (GEE) approach is commonly used to analyze binary, longitudinal data in the context of independent variables. However, the sequence of observations may be assumed to follow a Markov chain with stationary transition probabilities when observations are made at fixed time points. Participants favoring the transition to one particular state over the other would be evidence of a trend in the observations. Using a log-transformed trend parameter, the determinants of a trend in a binary, longitudinal study may be evaluated by maximizing the likelihood function. A new methodology is presented here to test for the presence and determinants of a trend in binary, longitudinal observations. Empirical studies are evaluated and comparisons are made with the GEE approach. Practical application of the proposed method is made to the data available from an intervention study on smoking cessation.

Cancer-Related News from the CDC: Cigarette Smoking among Adults and Trends in Smoking Cessation

Cancer-Related News from the CDC: Cigarette Smoking among Adults and Trends in Smoking Cessation

Educational inequalities in smoking cessation trends in Italy, 1982–2002

Background/aim:Smoking prevalence rates are declining in most industrialised countries, partly because of growing cessation rates. However, little is known on recent time-trends in smoking cessation by socioeconomic position. This study...

Scottish smoke‐free legislation and trends in smoking cessation

To investigate trends in smoking cessation before and after the introduction of Scottish smoke-free legislation and to assess the perceived influence of the legislation on giving up smoking and perceptions of the legislation in smokers. Longitudinal data on smoking cessation were obtained from 1998 to 2007 on a cohort of 3350 Scottish adults aged between 50 and 75 years at baseline. All members of the cohort were participating in a clinical trial of aspirin in people at moderately increased risk of cardiovascular events. A subgroup of 474 participants who had smoked in the year prior to the introduction of legislation in March 2006 also completed a questionnaire on the influence and perceptions of the smoke-free legislation following its introduction. Smoking status was recorded yearly, including dates of quitting and restarting. Participants who gave up smoking for at least 3 months were recorded as having quit smoking. The questionnaire included scales on whether the smoke-free legislation had helped/influenced cessation, made the individual think about/prompt them to quit and perceptions of the legislation. The odds of smokers quitting annually increased throughout the 7-year period prior to introduction of the smoke-free legislation to 2 years afterwards (odds ratio 1.09, 95% confidence interval 1.05-1.12, P<0.001). During 2006, the pattern of quarterly quitting rates changed, with an increase in quit rates (to 5.1%) in the 3-month period prior to introduction of the legislation (January-March 2006). Socio-economic status was not related to smoking cessation. In the subgroup completing the questionnaire (n=474), 57 quit smoking between June 2005 and May 2007 and 43.9% of these said that the smoke-free legislation had helped them to quit. Most (>70%) smokers were positive about the legislation, especially those from more affluent compared with more deprived communities (P=0.01). The Scottish smoke-free legislation was associated with an increase in the rate of smoking cessation in the 3-month period immediately prior to its introduction. Overall quit rates in the year the legislation was introduced and the subsequent year were consistent with a gradual increase in quit rates prior to introduction of the legislation. Socio-economic status was not related to smoking cessation, but individuals from more affluent communities were more positive about the legislation.

Widening social inequalities in smoking cessation in Spain, 1987–1997

In southern Europe, the prevalence of smoking among women has been lower than in northern Europe, with a wider gender and socioeconomic gap compared with most other developed countries. In...

The lung cancer epidemic in Australia, 1910 to 1989

Deaths that occurred in Australia between 1985 and 1989 that were ascribed to cancers of the respiratory tract and intrathoracic organs were obtained to update Australian lung cancer mortality trends. The age-standardised mortality rate from lung cancer in males decreased significantly from 49/100,000 in 1980-1984 to 46.4/100,000 in 1985-1989 (-5.5%). Lung cancer mortality in females increased significantly to 12.3/100,000 in 1985-1989 from an average of 10.7/100,000 in 1980-1984 (+15%). We conclude that lung cancer mortality in males is declining and although mortality in females continues to increase, there is evidence that the rate of increase has started to slow. The decline in male mortality has been anticipated from their trends in smoking cessation. The slowing increase in women cannot be ascribed to similar patterns of cessation. It is considered more likely to be due to decreasing trends in tar consumption linked to the tar content of preferred brands.