Susceptibility to Nicotine Dependence: The Development and Assessment of Nicotine Dependence in Youth 2 Study

McGill University, Montréal, Quebec, Canada
PEDIATRICS (Impact Factor: 5.47). 11/2007; 120(4):e974-83. DOI: 10.1542/peds.2007-0027
Source: PubMed


The purpose of this work was to identify characteristics that predict progression from the first inhalation of a cigarette to dependence. We studied a cohort of 1246 public school 6th-graders in 6 Massachusetts communities (mean age at baseline: 12.2 years).
We conducted a 4-year prospective study using 11 interviews. We assessed 45 risk factors and measured diminished autonomy over tobacco with the Hooked on Nicotine Checklist and evaluated tobacco dependence according to the International Classification of Diseases, 10th Revision. Cox proportional-hazards models were used.
Among 217 youths who had inhaled from a cigarette, the loss of autonomy over tobacco was predicted by feeling relaxed the first time inhaling from a cigarette and depressed mood. Tobacco dependence was predicted by feeling relaxed, familiarity with Joe Camel, novelty seeking, and depressed mood.
Once exposure to nicotine had occurred, remarkably few risk factors for smoking consistently contributed to individual differences in susceptibility to the development of dependence or loss of autonomy. An experience of relaxation in response to the first dose of nicotine was the strongest predictor of both dependence and lost autonomy. This association was not explained by trait anxiety or any of the other measured psychosocial factors. These results are discussed in relation to the theory that the process of dependence is initiated by the first dose of nicotine.

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    • "Recent national data suggest nearly half of all U.S. youths ages 12 – 18 have tried smoking during their lifetime and 20% have done so within the past month (CDC, 2010b). Many of these young people will go on to become lifetime smokers, as an estimated 90% of adult smokers initiate this habit before age 18 (Backinger, Fagan, Matthews, & Grana, 2003; DiFranza et al., 2007; Gilpin, Choi, Berry, & Pierce, 1999). These data highlight the critical need for effective adolescent smoking prevention strategies, including those which capitalize on naturally-occurring interests among young people, such as engaging in sports and other physical activities (deRuiter & Faulkner, 2006). "
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    ABSTRACT: Adolescent sports participants are less likely to smoke cigarettes, and sports participation may prevent young people from smoking. Research suggests that the relationship between sports participation and smoking may vary by race/ethnicity and is also possibly moderated by exposure to peer smoking. We investigated these relationships in a sample of 311 adolescents ages 13-21 presenting for well-visit medical appointments. Participants completed valid assessments of demographics, sports participation, exposure to peer smoking, and smoking behavior. The primary outcome was smoking status (never smoked, tried smoking, experimental/current smoker). Ordinal logistic regression was used separately for non-Hispanic White (n=122) and non-white (n=189; 70.4% black, 14.3% Hispanic, and 15.3% other) adolescents. Among White adolescents, sports participants had significantly lower odds of smoking than non-sports participants, independent of age, gender, and peer smoking. For non-Whites, the adjusted effect of sports participation on smoking depended upon exposure to peers who smoke. Compared with non-sport participants with no exposure to peer smoking, sports participants with no exposure to peer smoking had significantly lower odds of smoking, whereas sports participants with exposure to peer smoking had significantly higher odds of smoking. Sports appear to be protective against smoking among non-Hispanic White adolescents, but among non-White adolescents exposure to peer smoking influences this protection. Interventions incorporating sports to prevent smoking should consider these racial/ethnic differences to address disparities in smoking-related disease.
    Addictive behaviors 05/2012; 37(10):1114-21. DOI:10.1016/j.addbeh.2012.05.012 · 2.76 Impact Factor
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    • "In a study of craving patterns, tolerance, and subjective responses to the pharmacological effects of smoking, findings from Pomerleau et al. (2004) [16] indicated 20 cigarettes per lifetime may be a more prudent marker than 100 for such a differentiation. Others have proposed that liability for dependence and subsequent uptake of smoking may even be distinguishable after an individual's very first puff [17]. Additionally, non-daily and light daily smoking—behaviors consistent with current cigarette smoking but lifetime smoking <100 cigarettes—have been found to significantly vary across racial/ethnic subpopulations [18] [19] [20] [21] [22] [23] [24]. "
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    ABSTRACT: To compare prevalence estimates and assess issues related to the measurement of adult cigarette smoking in the National Health Interview Survey (NHIS) and the National Survey on Drug Use and Health (NSDUH). 2008 data on current cigarette smoking and current daily cigarette smoking among adults ≥18 years were compared. The standard NHIS current smoking definition, which screens for lifetime smoking ≥100 cigarettes, was used. For NSDUH, both the standard current smoking definition, which does not screen, and a modified definition applying the NHIS current smoking definition (i.e., with screen) were used. NSDUH consistently yielded higher current cigarette smoking estimates than NHIS and lower daily smoking estimates. However, with use of the modified NSDUH current smoking definition, a notable number of subpopulation estimates became comparable between surveys. Younger adults and racial/ethnic minorities were most impacted by the lifetime smoking screen, with Hispanics being the most sensitive to differences in smoking variable definitions among all subgroups. Differences in current cigarette smoking definitions appear to have a greater impact on smoking estimates in some sub-populations than others. Survey mode differences may also limit intersurvey comparisons and trend analyses. Investigators are cautioned to use data most appropriate for their specific research questions.
    Journal of Environmental and Public Health 05/2012; 2012(8):918368. DOI:10.1155/2012/918368
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    • "To our knowledge, two studies examined the effect of paternal parenting on child ND or heavy smoking. Contradictory findings were reported: getting along with father did not predict ND (DiFranza et al., 2007a), while father warmth and hostility predicted son's heavy smoking (White, Johnson, & Buyske, 2000). "
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    ABSTRACT: We investigated the role of psychosocial and proximal contextual factors on nicotine dependence in adolescence. Data on a multiethnic cohort of 6th to 10th graders from the Chicago public schools were obtained from four household interviews conducted with adolescents over two years and one interview with mothers. Structural equation models were estimated on 660 youths who had smoked cigarettes by the first interview. Pleasant initial sensitivity to tobacco use, parental nicotine dependence (ND), adolescent ND and extensiveness of smoking at the initial interview had the strongest total effects on adolescent ND two years later. Perceived peer smoking and adolescent conduct problems were of lesser importance. Parental ND directly impacted adolescent ND two years later and had indirect effects through pleasant initial sensitivity and initial extensiveness of smoking. Parental depression affected initial adolescent dependence and depression but adolescent depression had no effect on ND. The model had greater explanatory power for males than females due partly to the stronger effect of conduct problems on dependence for males than females. The findings underscore the importance of the initial drug experience and familial factors on adolescent nicotine dependence and highlight the factors to be the focus of efforts targeted toward preventing ND among adolescents.
    Journal of Child Psychology and Psychiatry 10/2011; 52(10):1063-72. DOI:10.1111/j.1469-7610.2010.02362.x · 6.46 Impact Factor
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