Distinct coping strategies differentially predict urge levels and lapses in a smoking cessation attempt

This study analysed mechanisms through which stress-coping and temptation-coping strategies were associated with lapses. Furthermore, we explored whether distinct coping strategies differentially predicted reduced lapse risk, lower urge levels, or a weaker association between urge levels and lapses during the first week of an unassisted smoking cessation attempt. Participants were recruited via the internet and mass media in Switzerland. Ecological momentary assessment (EMA) with mobile devices was used to assess urge levels and lapses. Online questionnaires were used to measure smoking behaviours and coping variables at baseline, as well as smoking behaviour at the three-month follow-up. The sample consisted of 243 individuals, aged 20 to 40, who reported 4199 observations. Findings of multilevel regression analyses show that coping was mainly associated with a reduced lapse risk and not with lower urge levels or a weaker association between urge levels and lapses. 'Calming down' and 'commitment to change' predicted a lower lapse risk and also a weaker relation between urge levels and lapses. 'Stimulus control' predicted a lower lapse risk and lower urge levels. Conversely, 'task-orientation' and 'risk assessment' were related to higher lapse risk and 'risk assessment' also to higher urge levels. Disengagement coping i.e. 'eating or shopping', 'distraction', and 'mobilising social support' did not affect lapse risk. Promising coping strategies during the initial stage of smoking cessation attempt are targeted directly at reducing the lapse risk and are characterised by engagement with the stressor or one's reactions towards the stressor and a focus on positive consequences instead of health risks.

Smoking behaviour, former quit attempts and intention to quit in urban adolescents and young adults: A five-year longitudinal study

OBJECTIVES: To examine smoking behaviour, former quit attempts and intention to quit among Swiss adolescents and young adults over five year's time. STUDY DESIGN: five-year longitudinal study (2003, 2005 and 2008) based on a random urban community sample (N = 1345 complete cases). METHODS: Data were collected by computer-assisted telephone interviews with adolescents (16-17) and young adults (18-24). Main outcome measures included self-reported smoking behaviour, former quit attempts, smoking cessation methods and current intentions to quit smoking. RESULTS: Adolescents were more often non-smokers and less often daily smokers when compared to young adults at baseline (χ(2)(4) = 28.68, P < .001). Their smoking behaviour increased significantly from baseline to follow-up (T = 1445.50, r = .20, P < .001) in contrast to the stable smoking behaviour in young adults (χ(2)(2) = .12, n.s.). In longitudinal analyses young adults were also more stable in their smoking status at the later measurement points. In comparison adolescents changed their smoking status more often being non-smokers at baseline and smokers later on. Independently of the age group, the majority of smokers already had previously attempted to quit (65%) or intended to give up smoking at some point (72%). However only 17% were motivated to make the quit attempt within the next 6 months. Self-quitting was the preferred method, and 25% of the self-quitters had been successful. CONCLUSION: This study illustrates that different developments in smoking behaviour exist in adolescents and young adults. Our study reveals that a majority of smokers are willing to quit but often fail. Furthermore, the data indicates that for adolescents the focus should lie on primary prevention.

Identifying Distinct Quitting Trajectories after an Unassisted Smoking Cessation Attempt: An Ecological Momentary Assessment Study

Objectives: This study aimed at identifying distinct quitting trajectories over 29 days after an unassisted smoking ces- sation attempt by ecological momentary assessment (EMA). In order to validate these trajectories we tested if they predict smoking frequency up to six months later. Methods: EMA via mobile phones was used to collect real time data on smoking (yes/no) after an unassisted quit attempt over 29 days. Smoking frequency one, three and six months after the quit attempt was assessed with online questionnaires. Latent class growth modeling was used to analyze the data of 230 self-quitters. Results: Four different quitting trajectories emerged: quitter (43.9%), late quitter (11.3%), returner (17%) and persistent smoker (27.8%). The quitting trajectories predicted smoking frequency one, three and six months after the quit attempt (all p < 0.001). Conclusions: Outcome after a smoking cessation attempt is better described by four distinct trajectories instead of a binary variable for abstinence or relapse. In line with the relapse model by Marlatt and Gordon, late quitter may have learned how to cope with lapses during one month after the quitting attempt. This group would have been allocated to the relapse group in traditional outcome studies.

Does cigarette smoking modify the association between change in body mass index during young adulthood and risk of coronary mortality during middle-age in men? Twenty-five year follow-up results from the Chicago Western Electric Study

Many persons in the U.S. gain weight during young adulthood, and the prevalence of obesity has been increasing among young adults. Although obesity and physical inactivity are generally recognized as risk factors for coronary heart disease (CHD), the magnitude of their effect on risk may have been seriously underestimated due to failure to adequately handle the problem of cigarette smoking. Since cigarette smoking causes weight loss, physically inactive cigarette smokers may remain relatively lean because they smoke cigarettes. We hypothesize cigarette smoking modifies the association between weight gain during young adulthood and risk of coronary heart disease during middle age, and that the true effect of weight gain during young adulthood on risk of CHD can be assessed only in persons who have not smoked cigarettes. Specifically, we hypothesize that weight gain during young adulthood is positively associated with risk of CHD during middle-age in nonsmokers but that the association is much smaller or absent entirely among cigarette smokers. The purpose of this study was to test this hypothesis. The population for analysis was comprised of 1,934 middle-aged, employed men whose average age at the baseline examination was 48.7 years. Information collected at the baseline examinations in 1958 and 1959 included recalled weight at age 20, present weight, height, smoking status, and other CHD risk factors. To decrease the effect of intraindividual variation, the mean values of the 1958 and 1959 baseline examinations were used in analyses. Change in body mass index ($\Delta$BMI) during young adulthood was the primary exposure variable and was measured as BMI at baseline (kg/m$\sp2)$ minus BMI at age 20 (kg/m$\sp2).$ Proportional hazards regression analysis was used to generate relative risks of CHD mortality by category of $\Delta$BMI and cigarette smoking status after adjustment for age, family history of CVD, major organ system disease, BMI at age 20, and number of cigarettes smoked per day. Adjustment was not performed for systolic blood pressure or total serum cholesterol as these were regarded as intervening variables. Vital status was known for all men on the 25th anniversary of their baseline examinations. 705 deaths (including 319 CHD deaths) occurred over 40,136 person-years of experience. $\Delta$BMI was positively associated with risk of CHD mortality in never-smokers, but not in ever-smokers (p for interaction = 0.067). For never-smokers with $\Delta$BMI of stable, low gain, moderate gain, and high gain, adjusted relative risks were 1.00, 1.62, 1.61, and 2.78, respectively (p for trend = 0.010). For ever-smokers, with $\Delta$BMI of stable, low gain, moderate gain, and high gain, adjusted relative risks were 1.00, 0.74, 1.07, and 1.06, respectively (p for trend = 0.422). These results support the research hypothesis that cigarette smoking modifies the association between weight gain and CHD mortality. Current estimates of the magnitude of effect of obesity and physical inactivity on risk of coronary mortality may have been seriously underestimated due to inadequate handling of cigarette smoking. ^

Cigarette smoking and Ecuadorian adolescents: A cross-sectional survey and policy review

This study investigates the relationship between cigarette smoking and adolescents in Ecuador, South America. Using the Social Learning Theory as a basis, the cross-sectional survey focuses attention on such social influences as the smoking habits of family members and peers as well as, the role of cigarette advertisements. Actual use prevalence, access to cigarettes and knowledge and attitudes about smoking are also obtained.^ The survey was conducted in both urban and rural areas, with 50 schools in 40 different communities participating. Two thousand four hundred and fifty-seven adolescents aged 9 to 15 years completed a self-administered questionnaire. This part of the study was conducted in collaboration with the international health organization Amigos de las Americas (AMIGOS). Staff assigned to the AMIGOS Ecuador projects worked with local health and education officials to implement the cross-sectional survey in the field.^ The key informant survey and subsequent policy review were designed to illuminate the social, cultural and institutional environment for anti-smoking activities and interventions in Ecuador. Key individuals involved with this issue on both national and local levels were interviewed. A review of past legislative efforts and present anti-smoking laws was also conducted.^ The current smoking prevalence among the study population was 8.6 percent. Findings from the cross-sectional survey revealed significant positive associations between the smoking habits of siblings and peers and the smoking behavior of the adolescents surveyed. Significant age and gender differences were also found in association with several different variables.^ The policy review found an unfavorable environment for anti-smoking efforts. Several factors contribute to this including, most importantly, lack of funding and lack of public support. The present anti-smoking law is often vague and lacks important provisions, such as a prohibition on selling tobacco products to minors.^ Together, the two surveys provide comprehensive information for the purpose of designing smoking prevention interventions. Using the results from the two surveys, recommendations for intervention are proposed. ^

A study of the impact of cigarette advertising on adolescent susceptibility to smoking among 5th-, 8th-, and 12th-grade students in Hempstead and Hitchcock Independent School Districts

This study assessed the impact of cigarette advertising on adolescent susceptibility to smoking in the Hempstead and Hitchcock Independent School Districts. A convenience sample of 217 youths, 10-19 years of age was recruited in the study. Students completed both a paper-and-pencil and a computer-aided questionnaire in April 1996. Adolescents were defined as susceptible to smoking if they could not definitely rule out the possibility of future smoking. For the analysis, an index was devised: a 5-point index of an individual's receptivity to cigarette advertising. The index is determined by the number of positive responses to five survey items (recognizing cigarette brand logos, recognizing cigarette advertisement's pictures, recognizing cigarette brand slogans, evaluating adolescent attitudes toward cigarette advertising, and the degree to which adolescents were exposed to cigarette advertisements). Using logistic regression, we assessed the independent importance of the index in predicting susceptibility to smoking and ever smoking after adjusting for sociodemographic variables, perceived school performance and family composition. Of students surveyed, 54.4% of students appeared to have started the smoking uptake process as measured by susceptibility to smoking. Camel was recognized by the majority of students (88%), followed by Marlboro (41.5%) and Newport (40.1%). The pattern for recognition of the cigarette advertisements was the same as the pattern of market for cigarette. Advertisement featuring the cartoon character Joe Camel was significantly more appealing to adolescents than were advertisements with human models, with animal models, and with text only (p $<$ 0.001). Text only advertisement was significantly less appealing than other types of advertisements. The cigarette advertisement with White models (Marlboro) had significantly higher appeal to White students than to African-American students (p $<$ 0.001). The cigarette advertisement featuring African-American models (Virginia Slims) was significantly more appealing to African-American students than other ethnic groups (p $<$ 0.001). Receptivity to cigarette advertising was to be an important concurrent predictor of past smoking experience and intention to smoke in the future. Adolescents who scored in the fourth quartile of the Index of Receptivity to Cigarette Advertising were 7.54 (95% confidence interval (CI) = 1.92-29.56) times as likely to be susceptible to smoking, and were 4.56 (95% CI = 1.55-13.38) times as likely to have tried smoking, as those who scored in the first quartile of the Index. The findings confirmed the hypothesis that cigarette advertising may be a strong current influence in encouraging adolescents to initiate the smoking uptake process than sociodemographic variables, perceived school performance and family composition. ^

The relationship of maternal low birthweight and infant low birthweight among African-American women at term delivery: Findings from the 1988 National Maternal and Infant Health Survey

A cohort study study design was used to study the relationship of maternal low birthweight and infant low birthweight among African American women delivering full term infants. The cohort consisted of 3,157 mother-infant pairs drawn from the 1988 National Maternal and Infant Health Survey conducted by the National Center for Health Statistics. The objectives of the study were (1) to determine if low birthweight, African American mothers delivering term infants experienced higher rates of infant low birthweight and (2) to examine the role of selected contributory variables in the relationship of maternal low birthweight and infant low birthweight. Contributory risk factors examined included maternal marital status, maternal age, maternal education, maternal height, maternal prepregnant weight, birth order, history of a prior low birthweight delivery, timing of prenatal care, number of prenatal visits, gestational length, infant gender, and behavioral factors of smoking, alcohol, and illicit drug use during pregnancy.^ Using logistic regression analysis, risk of infant low birthweight among maternal low birthweight mothers increased after controlling for less than a high school education, less than 20 years of age, prepregnant weight less than 100 lbs, history of a prior low birthweight delivery, birth order, smoking during pregnancy, and use of alcohol and illicit drugs during pregnancy, but was not statistically significant. Loss of statistical significance was attributed to a large reduction in cases available for analysis after including illicit drug use in the model.^ This study demonstrated a consistent pattern of increased rates of infant low birthweight among low birthweight mothers. The force of history remains, hence women with this trait should be carefully monitored and advised during pregnancy to decrease risk of a low birthweight infant, in order to decrease the chain of events leading to future generations of low birthweight mothers. ^

Hormonal risk factors and testicular cancer

The cause of testicular cancer is not known and recent hypotheses have suggested an altered hormonal milieu may increase the risk of testis cancer. This study examined modulation of testicular cancer risk by hormonal factors, specifically: environmental xenoestrogens (e.g. organochlorines), prenatal maternal estrogens, testosterone indices (age at puberty, severe adolescent acne, self-reported balding), sedentary lifestyle and dietary consumption of fats and phytoestrogens.^ A hospital based friend matched case-control study was conducted at the University of Texas M. D. Anderson Cancer Center in Houston, Texas, between January 1990 and October 1996. Cases had a first primary testis tumor diagnosed between age 18 to 50 years and resided in Texas, Louisiana, Oklahoma or Arkansas.^ Cases and friend controls completed a mail questionnaire and case/control mothers were contacted by phone regarding pregnancy related variables. The study population comprised 187 cases, 148 controls, 147 case mothers and 86 control mothers. Odds ratios were virtually identical whether the match was retained or dissolved, thus the analyses were conducted using unconditional logistic regression.^ Cryptorchidism was a strong risk factor for testis cancer with an age-adjusted odds ratio (OR) of 7.7 (95% confidence interval (CI): 2.3-26.3). In a final model (adjusted for age, education, and cryptorchidism), history of severe adolescent acne and self-reported balding were both significantly protective, as hypothesized. For acne (yes vs. no) the OR was 0.5 (CI: 0.3-1.0) and for balding (yes vs. no) the OR was 0.6 (CI: 0.3-1.0). Marijuana smoking was a risk factor among heavy, regular users (17 times/week, OR = 2.4; CI: 0.9-6.4) and higher saturated fat intake increased testis cancer risk (saturated fat intake $>$ 15.2 grams/day vs. $<$ 11.8 grams/day, OR = 3.3; CI: 1.5-7.1). Early puberty, xenoestrogen exposure, elevated maternal estrogen levels, sedentary lifestyle and dietary phytoestrogen intake were not associated with risk of testicular cancer.^ In conclusion, testicular cancer may be associated with endogenous androgen metabolism although environmental estrogen exposure can not be ruled out. Further research is needed to understand the underlying hormonal mechanisms and possible dietary influences. ^

Smoking, apolipoprotein E genotypes, and mortality (the Ludwigshafen RIsk and Cardiovascular Health study).

AIMS The genetic polymorphism of apolipoprotein E (APOE) has been suggested to modify the effect of smoking on the development of coronary artery disease (CAD) in apparently healthy persons. The interaction of these factors in persons undergoing coronary angiography is not known. METHODS AND RESULTS We analysed the association between the APOE-genotype, smoking, angiographic CAD, and mortality in 3263 participants of the LUdwigshafen RIsk and Cardiovascular Health study. APOE-genotypes were associated with CAD [ε22 or ε23: odds ratio (OR) 0.56, 95% confidence interval (CI) 0.43-0.71; ε24 or ε34 or ε44: OR 1.10, 95% CI 0.89-1.37 compared with ε33] and moderately with cardiovascular mortality [ε22 or ε23: hazard ratio (HR) 0.71, 95% CI 0.51-0.99; ε33: HR 0.92, 95% CI 0.75-1.14 compared with ε24 or ε34 or ε44]. HRs for total mortality were 1.39 (95% CI 0.39-0.1.67), 2.29 (95% CI 1.85-2.83), 2.07 (95% CI 1.64-2.62), and 2.95 (95% CI 2.10-4.17) in ex-smokers, current smokers, current smokers without, or current smokers with one ε4 allele, respectively, compared with never-smokers. Carrying ε4 increased mortality in current, but not in ex-smokers (HR 1.66, 95% CI 1.04-2.64 for interaction). These findings applied to cardiovascular mortality, were robust against adjustment for cardiovascular risk factors, and consistent across subgroups. No interaction of smoking and ε4 was seen regarding non-cardiovascular mortality. Smokers with ε4 had reduced average low-density lipoprotein (LDL) diameters, elevated oxidized LDL, and lipoprotein-associated phospholipase A2. CONCLUSION In persons undergoing coronary angiography, there is a significant interaction between APOE-genotype and smoking. The presence of the ε4 allele in current smokers increases cardiovascular and all-cause mortality.

Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.