Lung adenocarcinoma patients with ROS1-rearranged tumors by sex and smoking intensity

Background

ROS1 rearrangements (ROS1+) define a distinct molecular subset of lung adenocarcinomas. ROS1 + tumors are known to occur more in never-smokers, but the frequency and outcome of ROS1 positivity by sex and smoking intensity are not clearly documented.

Patients and methods

This patient cohort study included all never- (<100 cigarettes lifetime) and light- (100 cigarettes-20 pack-years) smokers, and a sample of heavy-smokers. ROS1 + rates by sex and smoking intensity were compared within and beyond our study. Survival outcomes were analyzed using Kaplan-Meier curves and Cox proportional hazards models.

Results

Of the 571 total patients, ROS1 + was detected in 24 (4.2%): 6.4% in men and 3.0% in women; 5.1% in never-, 5.7% in light-, and 1.8% in heavy-smokers (P=0.05). Among the 209 stage IIIB-IV patients, men had much higher ROS1 + rate (11.1%) not only than women (1.7%, P=0.004) in our study, but also than men (0.4%-1.8%) in 8 published studies (Ps = 0.0019-0.0001). ROS1+ rates were similar between never- (9.3%) and light-smokers (8.1%) and significantly lower in heavy-smokers (1.2%, P=0.017), a finding confirmed by 6 published studies (Ps = 0.041-0.0001). Overall survival of ROS1 + patients were significantly better than the ROS1- (P=0.023) mainly due to targeted therapy. Among patients who exhibited resistance to crizotinib, follow-up treatment of entrectinib and lorlatinib showed remarkable survival benefits.

Conclusions

The ROS1 + rates were higher in men than in women, and similar in never- and light-smokers, more pronounced in stage IIIB-IV patients. Newer-generation ALK/ROS1-targeted drugs showed efficacy in a cohort of crizotinib resistant ROS1 + patients. These results, when validated, could assist efficiently accruing ROS1 + patients.

Factors associated with smoking intensity among adult smokers: findings from the longitudinal cohort of the Tehran lipid and glucose study

BACKGROUND

Smoking is a significant public health problem, and there is a scarcity of documents regarding its severity, particularly in developing countries. This study aimed to determine factors related to the number of cigarettes consumed daily by adult smokers in Tehran.

METHODS

This study was conducted within the framework of the longitudinal study of Tehran Lipid and Glucose Study (TLGS). The study included 786 adult smokers living during four consecutive follow-ups from 2005 to 2016. The intensity of smoking was measured by the number of cigarettes consumed daily by adult smokers. Data analysis was done longitudinally and based on the mixed effects zero-inflated discrete Weibull (ZIDW) regression model.

RESULTS

The mean age of the individuals was 40.35 ± 12.68 years, and 643 (81.8%) of them were men. Also, 52.7% of individuals were daily smokers, 15.6% were occasional smokers, and 31.7% were non-smokers who became smokers during the study. Variables of age 1.005 (95%CI: 1.001-1.008), gender of male 1.196 (95%CI: 1.051-1.39), and marital status (divorced/widowed vs. single) 1.168 (95%CI: 1.015-1.39) were positively associated with smoking intensity. Education level (master and higher vs. illiterate) 0.675 (95%CI: 0.492-0.926)), employment status (student vs. unemployed) 0.683 (95%CI: 0.522-0.917), (housewife vs. unemployed) 0.742 (95%CI: 0.606-0.895), (Unemployed with income vs. unemployed) 0.804 (95%CI: 0.697, 0.923), implementation of smoking prohibition regulations (yes vs. no) 0.88 (95%CI: 0.843-0.932), and history of cardiovascular disease in male relatives (yes vs. no) 0.85 (95%CI: 0.771-0.951) were associated with lower smoking intensity.

CONCLUSION

We showed that demographic factors are associated with the intensity of smoking among adults and should be considered in policymakers' intervention programs to reduce smoking and quit smoking.

Prediction of lung cancer risk based on age and smoking history

BACKGROUND AND OBJECTIVE

The CISNET models provide predictions for dying of lung cancer in any year of life as a function of age and smoking history, but their predictions are quite variable and the models themselves can be complex to implement. Our goal was to develop a simple empirical model of the risk of dying of lung cancer that is mathematically constrained to produce biologically appropriate probability predictions as a function of current age, smoking start age, quit age, and smoking intensity.

METHODS

The six adjustable parameters of the model were evaluated by fitting its predictions of cancer death risk versus age to the mean of published predictions made by the CISNET models for the never smoker and for six different scenarios of lifetime smoking burden.

RESULTS

The mean RMS fitting error of the model was 6.16 × 10 ^-2 (% risk of dying of cancer per year of life) between 55 and 80 years of age. The model predictions increased monotonically with current age, quit age and smoking intensity, and decreased with increasing start age.

CONCLUSIONS

Our simple model of the risk of dying of lung cancer in any given year of life as a function of smoking history is easily implemented and thus may serve as a useful tool in situations where the mortality risks of smoking need to be estimated.

The estimated effect of graphic warning labels on smoker's intention to quit in Shanghai, China: a cross-sectional study

BACKGROUND

Tobacco consumption is the leading cause of death worldwide. Overwhelming studies demonstrate graphic warning labels (GWLs) on cigarette packs are effective in eliciting negative response to tobacco smoking, modifying beliefs about tobacco dangers, and increasing reported intention to quit, but the estimated effect of GWLs on smoking cessation intention among smokers is still limited in China. In this study, we aim to understand the smoking intensity, smoking duration and smoking cessation intention among current smokers, and to explore how their smoking cessation intention would be influenced by the GWLs in Shanghai.

METHODS

From January to June 2021, we totally recruited 1104 current smokers in Songjiang district and Fengxian district of Shanghai by multistage sampling design. We used Android pad assisted electronic questionnaire for data collection, and then implemented logistic regression for odds ratio (OR) and 95% confidence interval (CI) calculation to explore how smoking cessation intention would be influenced by the GWLs among current smokers.

RESULTS

One thousand one hundred four current smokers included 914 males (82.79%), with an average age of 43.61 years. 58.06% of current smokers reported smoking cessation intention due to GWLs. Logistic regression indicated a higher percentage of smoking cessation intention due to GWLs was among female smokers [OR = 2.41, 95% CI (1.61-3.59)], smokers with smoking intensity < 20 cigarette/day [OR = 1.92, 95% CI (1.44-2.55)], smokers with tobacco burden < 20% [OR = 1.94, 95% CI (1.35-2.79)], and among smokers had plan to quit in a year [OR = 6.58, 95% CI (4.71-9.18). Smokers with higher individual monthly income had lower percentage of smoking cessation intention (OR were 0.35, 0.46 and 0.41). Meanwhile, among 642 current smokers without plan to quit in a year, approximately 40% of them reported smoking cessation intention due to GWLs.

CONCLUSIONS

Smoking cessation intention due to the assumed GWLs on cigarette packs is high among current smokers in Shanghai, especially in female smokers, smokers with light tobacco burden and mild nicotine dependence. Incorporating smoking intensity as well as smoking burden into the implementation of GWLs as tobacco control measures would discourage smoking in China.

Racial disparities in intensity of smoke exposure and nicotine intake among low-dependence smokers

BACKGROUND

Compared to white smokers, Black smokers are at disproportionately higher risk for smoking-related disease, despite consuming fewer cigarettes per day (CPD). To examine racial disparities in biobehavioral influences on smoking and disease risk, we analyzed the relationship between self-reported tobacco dependence and intensity of tobacco smoke exposure per cigarette, on the one hand, and intensity of nicotine intake per cigarette, on the other.

METHODS

In 270 Black and 516 white smokers, smoke exposure was measured by expired carbon monoxide (CO), and nicotine intake was measured by plasma cotinine (COT) and cotinine+3'-hydroxycotinine ([COT + 3HC]). Using linear regression analyses, we analyzed how the Fagerström Test for Cigarette Dependence (FTCD) predicted intensity of smoke exposure per cigarette (CO/CPD) and intensity of nicotine intake per cigarette (COT/CPD; [COT + 3HC]/CPD), and how race moderated these relations.

RESULTS

Overall, Black smokers consumed fewer CPD than white smokers and had higher levels of CO/CPD, COT/CPD, and [COT + 3HC]/CPD. These elevations were most pronounced at lower levels of dependence: amongst Black smokers, FTCD negatively predicted intensity of smoke exposure as measured by CO/CPD (B = -0.12, 95% CI = -0.18, -0.05, p = 0.0003) and intensity of nicotine intake as measured by [COT + 3HC]/CPD (B = -1.31, 95% CI = -2.15, -0.46, p = 0.002).

CONCLUSIONS

Low-dependence Black smokers had higher intensities of both smoke exposure and nicotine intake per cigarette compared to similarly dependent white smokers, suggesting that measures of dependence, exposure, and intake underestimate incremental risk of each cigarette to Black smokers.

Determinants of smoking intensity in South Africa: Evidence from township communities

In order to analyze the smoking patterns in economically disadvantaged communities in South Africa, this paper examines the determinants of smoking intensity, using pooled data on price and non-price determinants of smoking from two cross-sectional surveys conducted in 2017 and 2018 to investigate the drivers of conditional cigarette demand among daily smokers. The analysis was done using a negative binomial regression. The results show that smokers reduce the number of cigarettes smoked daily when cigarette prices increase. The conditional price elasticity of cigarette demand of −0.295 for the overall sample shows that a 10% increase in cigarette price leads to a 2.95% decline in cigarette consumption among smokers. For young smokers, a 10% increase in cigarette price causes their smoking intensity to fall by 5%. Similar to other studies, the response of female smokers to cigarette price changes is statistically insignificant. Other factors affecting the conditional demand for cigarettes are education, race, single stick sales, gender, wealth, and age. We conclude that cigarette prices play a significant role in reducing smoking intensity among the South African poor. Since the magnitude of the price effect varies across age groups, races, and genders, the policy of higher tobacco excise taxes should be accompanied by interventions targeted at those less responsive to price-related measures.

Smokefree home rules and cigarette smoking intensity among smokers in different stages of smoking cessation from 20 low-and-middle income countries

Smokefree environment created by smokefree policies is associated with smoking reduction; however, there is paucity of literature on the relationship between smokefree home rules and smoking intensity in low-and-middle income countries (LMICs), and how smokefree policy affects smoking behavior of smokers at different stages of smoking cessation. This study examined the relationship between smokefree home rules and average number of cigarettes smoked per day (CPD) among daily smokers at different stages of the transtheoretical model (TTM) of change. Data from 18,718 current daily cigarette smokers from the Global Adult Tobacco Survey (GATS) conducted from 2011 to 2017 in 20 LMICs were analyzed. Weighted multivariable linear regression analyses were conducted using the log of CPD as the outcome variable with smokefree home rules as the exposure variable, controlling for selected covariates. Approximately 15% of the participants were in precontemplation, 5% were in preparation, 15% lived in partial smokefree homes, and 30% lived in complete smokefree homes. The average number of CPD was 12.3, 12.0, and 10.6 among participants living in homes where smoking was allowed, partial smokefree homes, and complete smokefree homes, respectively. Compared to living in homes where smoking was allowed, living in complete smokefree homes were associated with 22.5% (95%CI = 18.4%-26.5%), 17.9% (95%CI = 8.4%-27.3%), and 29.3% (95% CI = 17.1%-41.5%) fewer CPD among participants in precontemplation, contemplation, and preparation stages, respectively. These findings suggest that complete smokefree home policy will benefit smokers in LMICs irrespective of their intention to quit smoking in addition to protecting non-smokers from secondhand smoke exposure.

Integrative analysis of genetic and epigenetic profiling of lung squamous cell carcinoma (LSCC) patients to identify smoking level relevant biomarkers

Background

Incidence and mortality of lung cancer have dramatically decreased during the last decades, yet still approximately 160,000 deaths per year occurred in United States. Smoking intensity, duration, starting age, as well as environmental cofactors including air-pollution, showed strong association with major types of lung cancer. Lung squamous cell carcinoma is a subtype of non-small cell lung cancer, which represents 25% of the cases. Thus, exploring the molecular pathogenic mechanisms of lung squamous cell carcinoma plays crucial roles in lung cancer clinical diagnosis and therapy.

Results

In this study, we performed integrative analyses on 299 comparative datasets of RNA-seq and methylation data, collected from 513 lung squamous cell carcinoma cases in The Cancer Genome Atlas. The data were divided into high and low smoking groups based on smoking intensity (Numbers of packs per year). We identified 1002 significantly up-regulated genes and 534 significantly down-regulated genes, and explored their cellular functions and signaling pathways by bioconductor packages GOseq and KEGG. Global methylation status was analyzed and visualized in circular plot by CIRCOS. RNA-and methylation data were correlatively analyzed, and 24 unique genes were identified, for further investigation of regional CpG sites' interactive patterns by bioconductor package coMET. AIRE, PENK, and SLC6A3 were the top 3 genes in the high and low smoking groups with significant differences.

Conclusions

Gene functions and DNA methylation patterns of these 24 genes are important and useful in disclosing the differences of gene expression and methylation profiling caused by different smoking levels.

Factors associated with changing cigarette consumption patterns among low-intensity smokers: Longitudinal findings across four waves (2008-2012) of ITC Mexico Survey

Background

Light and intermittent smoking has become increasingly prevalent as smokers shift to lower consumption in response to tobacco control policies. We examined changes in cigarette consumption patterns over a four-year period and determined which factors were associated with smoking transitions.

Methods

We used data from a cohort of smokers from the 2008–2012 ITC Mexico Survey administrations to investigate transitions from non-daily (ND; n = 669), daily light (DL; ≤5 cigarettes per day (cpd); n = 643), and daily heavy (DH; >5 cpd; n = 761) smoking patterns. To identify which factors (i.e., sociodemographic measures, perceived addiction, quit behavior, social norms) were associated with smoking transitions, we stratified on smoking status at time t (ND, DL, DH) and used multinomial (ND, DL) and binomial (DH) logistic regression to examine transitions (quitting/reducing or increasing versus same level for ND and DL, quitting/reducing versus same level for DH).

Results

ND smokers were more likely to quit at follow-up than DL or DH smokers. DH smokers who reduced their consumption to ND were more likely to quit eventually compared to those who continued as DH. Smokers who perceived themselves as addicted had lower odds of quitting/reducing smoking consumption at follow-up compared to smokers who did not, regardless of smoking status at the prior survey. Quit attempts and quit intentions were also associated with quitting/reducing consumption.

Conclusions

Reducing consumption may eventually lead to cessation, even for heavier smokers. The findings that perceived addiction and quit behavior were important predictors of changing consumption for all groups may offer insights into potential interventions.

•

Smoking transitions were evaluated in a cohort of Mexican smokers.

•

The cohort consisted mostly of understudied light and intermittent smokers (LITS).

•

Reductions in smoking intensity were found to facilitate smoking cessation.

•

Greater perceived addiction inhibited cessation for smokers at all levels of intensity.

•

LITS patterns warrant attention as number of low-intensity smokers worldwide grows.

Determinants of cigarette smoking and smoking intensity among adult males in Ghana

BACKGROUND

In spite of the adverse health and financial implications of smoking, it still remains one of the leading causes of preventable diseases and deaths in the world. Key to discouraging the habit of smoking is knowledge of the drivers of smoking. In Ghana, though smoking behaviours are relatively more associated with adult males than youth and adolescents, studies on smoking behaviours of adult males are scant. This study, therefore, investigates the determinants of cigarette smoking and smoking intensity among adult males in Ghana.

METHODS

Data were obtained from the most recent Ghana Demographic and Health Survey (DHS) conducted in 2014. Based on the 2014 GDHS, a negative binomial-logit hurdle model was estimated to explore the socioeconomic and demographic characteristics associated with cigarette consumption and smoking intensity among adult males in Ghana. To ensure robustness, separate estimations were performed for the respective logit and negative binomial models used in the two-part model.

RESULTS

We find that men in lower socioeconomic category (poor and low education) have a higher likelihood to smoke. Also, age proved significant in explaining smoking behaviors in Ghana. Moreover, religion and region of residence are reported to affect cigarette consumption decision. Furthermore, we find that among the men who smoke, those between the ages of 44 and 60 years and have attained approximately primary education have a higher likelihood to smoke greater quantities of cigarette daily. Also, the smokers who reside in the Upper East and Upper West regions are reported to smoke more intensely than their counterparts in the Greater Accra region.

CONCLUSION

Since smoking remains one of the major causes of diseases and deaths the world over, the current study provides recent empirical evidence based on a nationally representative sample for public health policies geared towards smoking reduction and ultimately cessation. This study suggests that public policies that promote higher educational attainment and improved incomes (wealth) are crucial in smoking reduction and cessation in Ghana.

E-cigarette use and quantity of cigarette smoking among adolescent cigarette smokers: A finite mixture model analysis

BACKGROUND

E-cigarette use is popular among adolescents and youth, but its long-term public health implications remain largely unknown. Much of the literature has focused on understanding the relationship between e-cigarette use and youth cigarette initiation. However, very little is known about e-cigarette use and cigarette quantity among those who continue to smoke cigarettes. The objective of the present study was to examine the association between current e-cigarette use and quantity of cigarette smoking.

METHODS

Cross-sectional data on current smokers were drawn from the 2014-2015 Canadian Student Tobacco, Alcohol and Drugs Survey among high school students (n = 1411). A finite mixture model (FMM) was employed to account for unobserved heterogeneity due to clusters of finite sub-populations.

RESULTS

Current e-cigarette users reported smoking more conventional cigarettes in the past week compared to non-e-cigarette users (t [1409] = 4.7998; p < 0.001 in unadjusted analysis). Results from a finite mixture regression showed that current e-cigarette use was significantly associated with the number of cigarettes smoked in the past week, but only among light smokers (IRR = 1.40; CI = 1.05-1.85). However, additional analyses found that the association between e-cigarette use and quantity of cigarette smoked varied by individual smoking pattern. An FMM with a group or class modelling using individual smoking pattern showed a weaker association between e-cigarette use and quantity of cigarette smoking.

CONCLUSION

Findings of this study suggest that the significant association between e-cigarette use and quantity of cigarette smoking may be driven by patterns of use among experimental or beginner smokers.

Smoking quantity determines disease activity and function in Chinese patients with ankylosing spondylitis

The objective of this study was to systemically and comprehensively evaluate the associations between smoking and disease outcomes in patients with ankylosing spondylitis (AS). Information on smoking, clinical features, and sociodemographic characteristics was collected by a questionnaire administered directly to the patient. Group differences were analyzed by t test or chi-square test. Logistic regression analysis was conducted with the Bath AS Disease Activity Index (BASDAI), Bath AS Functional Index (BASFI), C-reactive protein, and erythrocyte sedimentation rate as the dependent variables and different stratification of smoking duration, smoking intensity, and cumulative smoking as independent variables. In order to compare our results with previous studies, meta-analysis was performed to calculate standardized mean difference (SMD) for relationship between outcomes and smoking status. A total of 1178 AS patients were analyzed. Compared with non-smokers, the risk of having active disease (BASDAI ≥ 4) was higher in patients who smoked at least 15 years, or 15 cigarettes per day, or 15 pack-years (OR = 1.70 [1.06, 2.73], 1.75 [1.08, 2.82], and 1.97 [1.06, 3.67], respectively); and smokers had increasing risk of BASDAI ≥ 4 with increasing years of smoking, or cigarettes per day, or pack-years (p_-trend = 0.010, 0.008 and 0.006, respectively). The risk of having active disease was higher in patients who smoked at least 15 cigarettes per day or 15 pack-years (OR = 1.74 [1.06, 2.84] and 2.89 [1.56, 5.35], respectively), with increasing number of cigarettes per day and pack-years. Smokers had an increased risk of BASFI ≥ 4 (p_-trend = 0.040 and 0.007, respectively). By meta-analysis, current, former and ever smokers had significantly higher BASDAI (SMD = 0.34 [0.18, 0.48], 0.10 [0.01, 0.19], and 0.27 [0.20, 0.34], respectively) and BASFI (SMD = 0.35 [0.16, 0.55], 0.30 [0.22, 0.39], and 0.35 [0.21, 0.50], respectively) compared to non-smokers. Smoking is a risk factor for greater disease activity and worse functioning in AS patients.

The relationship between smoking intensity and subclinical cardiovascular injury: The Multi-Ethnic Study of Atherosclerosis (MESA)

BACKGROUND AND AIMS

Modern tobacco regulatory science requires an understanding of which biomarkers of cardiovascular injury are most sensitive to cigarette smoking exposure.

METHODS

We studied self-reported current smokers from the Multi-Ethnic Study of Atherosclerosis. Smoking intensity was defined by number of cigarettes/day and urinary cotinine levels. Subclinical cardiovascular injury was assessed using markers of inflammation [high-sensitivity C-reactive protein (hsCRP), interleukin 6 & 2 (IL-2 & IL-6), tumor necrosis factor alpha (TNF-α)], thrombosis (fibrinogen, D-dimer, homocysteine), myocardial injury (troponin T; TnT), endothelial damage (albumin: creatinine ratio), and vascular function [aortic & carotid distensibility, flow-mediated dilation (FMD)]. Biomarkers were modeled as absolute and percent change using multivariable-adjusted linear regression models adjusted for cardiovascular risk factors and smoking duration.

RESULTS

Among 843 current smokers, mean age was 58 (9) years, 53% were men, 39% were African American, mean number of cigarettes per day was 13 (10), and median smoking duration was 39 (15) years. Cigarette count was significantly associated with higher hsCRP, IL-6 and fibrinogen (β coefficients: 0.013, 0.011, 0.60 respectively), while ln-transformed cotinine was associated with the same biomarkers (β coefficients: 0.12, 0.04, 5.3 respectively) and inversely associated with aortic distensibility (β coefficient: -0.13). There was a limited association between smoking intensity and homocysteine, D-dimer, and albumin:creatinine ratio in partially adjusted models only, while there was no association with IL-2, TNF-α, carotid distensibility, FMD, or TnT in any model. In percent change analyses, relationships were strongest with hsCRP.

CONCLUSIONS

Smoking intensity was associated with early biomarkers of CVD, particularly, markers of systemic inflammation. Of these, hsCRP may be the most sensitive.

Does neighborhood social cohesion modify the relationship between neighborhood social norms and smoking behaviors in Mexico?

The aim of this study was to examine the separate and combined relationships of neighborhood social norms and neighborhood social cohesion with smoking behavior in a cohort of adult Mexican smokers. Neighborhood anti-smoking norms were measured as the proportion of residents in each neighborhood who believed that society disapproves of smoking. Perceived social cohesion was measured using a 5-item cohesion scale and aggregated to the neighborhood level. Higher neighborhood anti-smoking norms were associated with less successful quitting. Neighborhood social cohesion modified the relationship between neighborhood social norms and two smoking behaviors: smoking intensity and quit attempts. Residents of neighborhoods with weaker anti-smoking norms and higher social cohesion had lower smoking intensity and more quit attempts than residents living in other areas. Social cohesion may help buffer smoking behavior in areas with weak social norms.

Working time and cigarette smoking: evidence from Australia and the United Kingdom

Cigarette smoking is a risk factor in a range of serious diseases, including cardiovascular disease, cancer, stroke and type II diabetes. Theory suggests that working long hours will increase smoking propensities among workers. Consequently there is a significant body of evidence on the relationship between working time and smoking. Results, however, are inconsistent and therefore inconclusive. This paper provides new evidence on how working time affects smoking behaviour using nationally representative panel data from Australia (from 2002 to 2011) and the United Kingdom (from 1992 to 2011). We exploit the panel design of the surveys to look at within-person changes in smoking behaviour over time as working time changes. In contrast to most previous studies, this means we control for time invariant aspects of personality and genetic inheritance that may affect both smoking propensities and choice of working hours. We find that working long hours tends to increase the chances that former smokers will relapse, reduce the chances that smokers will quit and increase cigarette consumption among regular smokers, and that these effects tend to become more pronounced for workers who usually work very long hours (50 or more hours a week) compared to those who work moderately long hours (40-49 h a week).

Gender differences in cigarette consumption in Turkey: evidence from the Global Adult Tobacco Survey

OBJECTIVE

The aim of this study is to examine the potential factors associated with both smoking participation and the level of cigarette consumption in Turkey from a gender perspective, the understanding of which are crucial to the formulation and implementation of anti-smoking policies.

METHODS

The Global Adult Tobacco Survey for 2008 is used in the analysis. Since the dependent variable, the number of cigarettes smoked per day, consists of nonnegative integer values, Negative Binomial and Zero-inflated Negative Binomial models are used as an estimation methodology. The zero-inflated model allows the interpretation of smoking propensity and smoking intensity behaviours separately.

RESULTS

The main findings of this study are twofold. First, the factors affecting the smoking behaviour of males and females are different. Second, there are also differences between the factors affecting the decisions of whether to smoke and how much to smoke for both genders. Cigarette prices, for example, affect the level of cigarette consumption of females but not of males whereas pro-cigarette marketing affects the decision of how much to smoke for males with no effect on female smoking.

CONCLUSIONS

The findings highlight the importance of gender differences in cigarette consumption. Overall, education programs, cigarette taxation and tobacco advertising bans have different effects on each gender whereas social interaction is important for cigarette smoking behaviour of both genders. The anti-smoking policies can be more effective if policy makers take into account gender differences in both smoking propensity and intensity.