How well does the index of receptivity to tobacco industry promotion discriminate between smoking and never smoking adolescents.

Tobacco advertising is often named as the culprit that causes children to start smoking (Lancaster & Lancaster, 2003). This belief can partly be attributed to the Index of Receptivity to Tobacco Industry Promotion (IRTIP) developed by Evans, Farkas, Gilpin, Berry, & Pierce (1995). IRTIP was later modified and used by Pierce, Choi, Gilpin, Farkas, & Berry (1998) in a longitudinal study that claimed to have found a causal link between advertising and adolescent cigarette trial. The model is advertised by the American National Cancer Institute (2004) as being able to measure the likelihood of an adolescent starting smoking. Because of Pierce’s causality claim and this endorsement, IRTIP has been widely adopted by tobacco-control researchers. Consequently, the results from IRTIP based surveys have played a central role in influencing tobacco control policy. Based on the logic that a model used to predict the chances of a non-smoker becoming a smoker should be able to distinguish between these two groups, discriminant analysis with dummy coded variables was used to validate IRTIP. The results show that while IRTIP classifies never-smokers well, it grossly misclassifies smokers. This leads to questions about the validity of the model and of studies using IRTIP.

The influence of parents, siblings and peers on pre- and early-teen smoking : a multilevel model

Introduction and Aims. Despite considerable success in tobacco control, many teenagers in Australia and other industrialised countries still smoke tobacco. There is mixed evidence on the relative influence of proximal social networks (parents/siblings/peers) on pre- and early-teen smoking, and no research has examined how these influences compare after accounting for school- and community-level effects.The aim of this study was to compare the relative influences of parents, siblings and peers, after accounting for school- and community-level variation in smoking.

Design and Methods. A cross-sectional fixed and random effects model of smoking prevalence was used, with individuals (n = 7314) nested within schools (n = 231) nested within communities (n = 30). Grade 6 and 8 students (modal ages 11 and 13 years) completed an on-line survey. Key variables included parent/sibling/peer use. Controls included alcohol involvement, sensation seeking, pro-social beliefs, laws/norms about substance use and school commitment.

Results.There was significant variation in smoking at both the school and community levels, supporting the need for a multilevel model. Individual-level predictors accounted for much of the variance at higher levels. The strongest effects were for number of friends who smoke, sibling smoking and alcohol involvement. Smaller significant effects were found for parent smoking. At the community level, socioeconomic disadvantage was significant, but community-level variance in pro-social and drug-related laws/norms was not related to smoking.

Discussion and Conclusions. Cross-level interactions were generally non-significant. Early teenage smoking was best explained by sibling and peer smoking, and individual risks largely accounted for the substantial variation observed across schools and communities. In terms of future tobacco control, findings point to the utility of targeting families in disadvantaged communities.[Kelly AB, O'Flaherty M, Connor JP, Homel R, Toumbourou JW, Patton GC, Williams J. The influence of parents, siblings and peers on pre- and early-teen smoking: A multilevel model.

Association of adolescent symptoms of depression and anxiety with daily smoking and nicotine dependence in young adulthood : findings from a 10-year longitudinal study

Aims To examine the association of adolescent depression and anxiety symptoms with daily smoking and nicotine dependence in young adulthood.

Design A prospective cohort study of adolescent and young adult health (n = 1943). Teen assessments occurred at 6-monthly intervals, with two follow-up assessments in young adulthood (wave 7, 1998; wave 8, 2001–03).

Setting Victoria, Australia.

Participants Students who participated at least once during the first six (adolescent) waves of the cohort study.

Measurements Adolescent depression and anxiety symptomswere assessed using the Revised Clinical Interview Schedule (CIS-R).Young adult tobacco usewas defined as: daily use (6 or 7 days perweek) and dependent use (>4 on the Fagerstrom Test for Nicotine Dependence).

Findings Among adolescent ‘less than daily’ smokers, those with high levels of depression and anxiety symptoms had an increased risk of reporting nicotine dependence in young adulthood [odds ratio (OR) 3.3, 95% confidence interval (CI) 1.2–9.1] compared to young adults who had low levels of adolescent depression and anxiety symptoms, after adjusting for potential confounding factors. Similarly, in the adjusted model (OR 1.9, 95% CI 1.0–3.4), among adolescent ‘daily’ smokers, those with high levels of depression and anxiety symptoms had an almost two-fold increase in the odds of reporting nicotine dependence in young adulthood compared to young adults with low levels of adolescent depression and anxiety symptoms.

Conclusions Adolescent smokerswith depression and anxiety symptoms are at increased risk for nicotine dependence into young adulthood. They warrant vigilance from primary care providers in relation to tobacco use well into adulthood.

Association between dependent smoking and a polymorphism in the tyrosine hydroxylase gene in a prospective population-based study of adolescent health

This study reports pilot data on an association between tobacco dependence and a five-allele tetranucleotide repeat polymorphism in the first intron of the tyrosine hydroxylase (TH) gene. One hundred and twenty-six Australian adolescents who had participated in the Health in Transition Study (1993–1997), and who showed patterns of either dependent or nondependent smoking across four waves of data collection, consented to participation in the pilot study. The smoking status of those recruited was confirmed using a telephone-administered drug use questionnaire during 2000. Tobacco dependence was defined as smoking more than 6 days per week and more than 10 cigarettes per day during wave 5 (year 2000) and at lfeast one prior wave (n = 58). A second, more stringent phenotype included smoking within an hour of waking (n = 37). The control group comprised adolescents who had used tobacco but had remained low-level social smokers across each wave of data (n = 56). DNA was collected using a mouthwash procedure. Using the more strictly defined tobacco dependence phenotype, and after adjusting for sex, a significant protective association was found between the K4 allele and tobacco dependence (OR 0.27, 95% confidence interval [CI] 0.09, 0.82). No association was found using the liberal criteria of tobacco dependence (OR 0.51, 95% confidence interval [CI] 0.23, 1.2). These preliminary results replicate a previous association between tobacco use and the K4 allele of the TH gene (Lerman et al., 1997). The potential significance of including time to first cigarette in definitions of tobacco dependence and the possible role that these TH variants might play in tobacco dependence are discussed.

Associations between smoking status, lifestyle and lipoprotein subclasses

Background: Although the relationship between cigarette smoking and cardiovascular disease (CVD) is well-established, the underlying mechanisms remain unclear. Smokers have a more atherogenic lipid profile but this may be mediated by lifestyle-related factors. Because detailed analysis of lipoprotein subclasses using nuclear magnetic resonance spectroscopy (NMR) may improve characterisation of lipid abnormalities, we applied the technique to investigate the relationships between smoking status, other lifestyle-related risk factors and lipoproteins in a contemporary cohort.

Methods: A total of 612 participants (360 women) aged 40-69 years at baseline (1990-1994) enrolled in the community-based Melbourne Collaborative Cohort Study had plasma lipoproteins measured using NMR. Data were analysed separately for men and women.

Results: After adjusting for other lifestyle-related risk factors, mean total low-density lipoprotein (LDL) particle concentration was higher for female smokers than non-smokers. Both medium and small LDL particle concentrations contributed to this difference. Both total high-density lipoprotein (HDL) and large HDL particle concentrations were lower for female smokers than non-smokers. The proportion at increased risk (according to NMR-determined particle size and number) was higher for female smokers than non-smokers. For men, there were few differences in lipoprotein measures related to smoking.

Conclusions: Female smokers have a more atherogenic lipoprotein profile than non-smokers, and this difference is independent of lifestyle-related risk factors. Lipoprotein profiles did not differ greatly between male smokers and non-smokers. These data reinforce the importance for women of not smoking.

Age at quitting smoking as a predictor of risk of cardiovascular disease incidence independent of smoking status, time since quitting and pack-years

Background: Risk prediction for CVD events has been shown to vary according to current smoking status, pack-years smoked over a lifetime, time since quitting and age at quitting. The latter two are closely and inversely related. It is not known whether the age at which one quits smoking is an additional important predictor of CVD events. The aim of this study was to determine whether the risk of CVD events varied according to age at quitting after taking into account current smoking status, lifetime pack-years smoked and time since quitting.
Findings. We used the Cox proportional hazards model to evaluate the risk of developing a first CVD event for a cohort of participants in the Framingham Offspring Heart Study who attended the fourth examination between ages 30 and 74 years and were free of CVD. Those who quit before the median age of 37 years had a risk of CVD incidence similar to those who were never smokers. The incorporation of age at quitting in the smoking variable resulted in better prediction than the model which had a simple current smoker/non-smoker measure and the one that incorporated both time since quitting and pack-years. These models demonstrated good discrimination, calibration and global fit. The risk among those quitting more than 5 years prior to the baseline exam and those whose age at quitting was prior to 44 years was similar to the risk among never smokers. However, the risk among those quitting less than 5 years prior to the baseline exam and those who continued to smoke until 44 years of age (or beyond) was two and a half times higher than that of never smokers.
Conclusions: Age at quitting improves the prediction of risk of CVD incidence even after other smoking measures are taken into account. The clinical benefit of adding age at quitting to the model with other smoking measures may be greater than the associated costs. Thus, age at quitting should be considered in addition to smoking status, time since quitting and pack-years when counselling individuals about their cardiovascular risk.

Framingham risk prediction equations for incidence of cardiovascular disease using detailed measures for smoking

Current prediction models for risk of cardiovascular disease (CVD) incidence incorporate smoking as a dichotomous yes/no measure. However, the risk of CVD associated with smoking also varies with the intensity and duration of smoking and there is a strong association between time since quitting and the risk of disease onset. This study aims to develop improved risk prediction equations for CVD incidence incorporating intensity and duration of smoking and time since quitting. The risk of developing a first CVD event was evaluated using a Cox’s model for participants in the Framingham offspring cohort who attended the fourth examination (1988–92) between the ages of 30 and 74 years and were free of CVD (n=3751). The full models based on the smoking variables and other risk factors, and reduced models based on the smoking variables and non-laboratory risk factors demonstrated good discrimination, calibration and global fit. The incorporation of both time since quitting among past smokers and pack-years among current smokers resulted in better predictive performance as compared to a dichotomous current/non-smoker measure and a current/quitter/never smoker measure. Compared to never smokers, the risk of CVD incidence increased with pack-years. Risk among those quitting more than five years prior to the baseline exam and within five years prior to the baseline exam were similar and twice as high as that of never smokers. A CVD risk equation incorporating the effects of pack-years and time since quitting provides an improved tool to quantify risk and guide preventive care.

Cigarette smoking, nicotine dependence and anxiety disorders : a systematic review of population-based, epidemiological studies

Background Multiple studies have demonstrated that rates of smoking and nicotine dependence are increased in individuals with anxiety disorders. However, significant variability exists in the epidemiological literature exploring this relationship, including study design (cross-sectional versus prospective), the population assessed (random sample versus clinical population) and diagnostic instrument utilized.

Methods We undertook a systematic review of population-based observational studies that utilized recognized structured clinical diagnostic criteria (Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD)) for anxiety disorder diagnosis to investigate the relationship between cigarette smoking, nicotine dependence and anxiety disorders.

Results In total, 47 studies met the predefined inclusion criteria, with 12 studies providing prospective information and 5 studies providing quasiprospective information. The available evidence suggests that some baseline anxiety disorders are a risk factor for initiation of smoking and nicotine dependence, although the evidence is heterogeneous and many studies did not control for the effect of comorbid substance use disorders. The identified evidence however appeared to more consistently support cigarette smoking and nicotine dependence as being a risk factor for development of some anxiety disorders (for example, panic disorder, generalized anxiety disorder), although these findings were not replicated in all studies. A number of inconsistencies in the literature were identified.

Conclusions Although many studies have demonstrated increased rates of smoking and nicotine dependence in individuals with anxiety disorders, there is a limited and heterogeneous literature that has prospectively examined this relationship in population studies using validated diagnostic criteria. The most consistent evidence supports smoking and nicotine dependence as increasing the risk of panic disorder and generalized anxiety disorder. The literature assessing anxiety disorders increasing smoking and nicotine dependence is inconsistent. Potential issues with the current literature are discussed and directions for future research are suggested.

Moral antecedents of smoking behavior and risk beliefs among overseas Asian students

Instead of focusing on the misconduct of multinational cigarette manufacturers, this research project broadens the discussion of cigarette consumption by focusing on the moral antecedent variables that shape young adults' smoking behavior and risk beliefs. It especially challenges current wisdom among anti-smoking advocates that by increasing consumer knowledge of the medical risks associated with smoking will lead to significant reductions in young adult smoking prevalence rates. Empirical results of this study suggest that although increasing smoking risk knowledge does not significantly reduce Asian students' smoking behavior, increasing their risk assessment beliefs does produce the desirable public policy effect of reducing current smoking. Furthermore, only among rules-driven individuals does an increase in no harm scores significantly reduce student smoking risk assessment beliefs. Thus, current anti-smoking advertising campaigns among overseas Asian students may be more effective if they attempt to change these students' smoking risks assessment beliefs especially if they are targeted to rules-driven student market segments.

Smokers and ex-smokers reaction to anti-smoking advertising : a mixed methods approach

Anti-smoking advertising is a central component of modern public health policy. Nevertheless, some smokers have reported that viewing anti-smoking advertising provokes intense nicotine craving. Anti-smoking advertising frequently features images of cigarettes and of individuals smoking. However, research indicates that images of tobacco paraphernalia may induce cravings in individuals addicted to nicotine. The effects of the presence of smoking cues in anti-smoking advertising were considered in the present study. Smokers and ex-smokers (N=63) were randomly assigned to view an anti-smoking advertisement or to complete a control task. Urge to smoke was measured pre- and post-test. Qualitative responses to anti-smoking advertising were also elicited from all participants in the intervention groups. According to both qualitative and quantitative data analyses viewing anti-smoking advertising, even with images of smoking related paraphernalia, led to decreases in craving amongst smokers. Ex-smokers experienced no change in quantitatively measured craving after viewing anti-smoking advertising. These findings are inconsistent with findings from studies using neutral or positive smoking cues. Qualitative data shows that no smokers or ex-smokers who viewed anti-smoking advertising reported an increase in tobacco craving as a result of viewing the campaign. Implications of these findings for future research and anti-smoking campaigns are discussed.