Published online October 1, 2007
PEDIATRICS Vol. 120 No. 4 October 2007, pp. e974-e983 (doi:10.1542/10.1542/peds.2007-0027)
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ARTICLE

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

Joseph R. DiFranza, MDa, Judith A. Savageau, MPHa, Kenneth Fletcher, PhDa, Lori Pbert, PhDb, Jennifer O'Loughlin, PhDc, Ann D. McNeill, PhD, PGCEd, Judith K. Ockene, PhDb, Karen Friedman, BAa, Jennifer Hazelton, BAa, Connie Wood, MSWa, Gretchen Dussault, BSa and Robert J. Wellman, PhDa,e

a Departments of Family Medicine and Community Health
b General Medicine, University of Massachusetts Medical School, Worcester, Massachusetts
c Department of Epidemiology and Biostatistics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
d University College London, London, United Kingdom
e Department of Psychology, Fitchburg State College, Fitchburg, Massachusetts


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
OBJECTIVES. 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).

METHODS. 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.

RESULTS. 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.

CONCLUSIONS. 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.

Key Words: nicotine • tobacco • adolescents • addiction • dependence

Abbreviations: DANDY—Development and Assessment of Nicotine Dependence in Youth • HONC—Hooked on Nicotine Checklist • ICD-10—International Classification of Diseases, Tenth Revision • HR—hazard ratio • ADHD—attention-deficit/hyperactivity disorder • CI—confidence interval

In the Development and Assessment of Nicotine Dependence in Youth 1 (DANDY-1) study, it was reported that youths differ widely in their susceptibility to dependence. Although most develop symptoms rapidly after the onset of tobacco use, others do not.1 With the DANDY-2 we sought to identify factors that determine susceptibility to nicotine dependence.

Previous research has identified many psychological factors that increase the risk of smoking. These include trait anxiety2,3; attention-deficit disorder4,5; attitudes and beliefs about the benefits of smoking6; poor school performance7; disaffection from families, schools, communities and religion8–11; poor coping skills11; depressed mood12–14; impulsiveness15; external locus of control16; low self-esteem16; novelty seeking; and risk taking.11 Social-environmental factors also play a role: these include access to tobacco17; exposure to parents, siblings, and peers who smoke or approve of smoking3,18–21; smoking in the home22; low socioeconomic status23; and exposure to tobacco marketing18,24 or smoking in entertainment media.20

The subjective effect of the first cigarette has predicted future smoking status in several studies.25–29 However, most of them relied on retrospective data collection, and none controlled for factors, such as personality, that might contribute to either the experience or the reporting of it. In the DANDY-1 study, only 22% of subjects experienced relaxation the first time they inhaled, but those who did went on to develop twice as many symptoms of nicotine dependence.30

We evaluated the roles of personality, environment, and the subjective response to nicotine in determining which youths get hooked once they have exposed their brains to nicotine by inhaling from a cigarette.


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 
We conducted a 4-year longitudinal study with a cohort of 6th-grade students. All of the procedures were approved by the University of Massachusetts Medical School Institutional Review Board and local school administrators.

Study Population
Subjects were recruited from grade schools in 6 Massachusetts communities to provide a racially diverse nonprobability sample. The study was publicized through school announcements, parent-teacher organizations, letters to parents, and presentations to classes and assemblies. Students informed their parents of their interest in the study, and we obtained parental consent either in writing or by telephone. Subjects provided assent at the time of enrollment. At each interview, subjects received their choice of a movie ticket, gift certificate, pen, or pencil. The only exclusion criterion was an inability to communicate in English. Because early initiation leads to stronger dependence,31 subjects were not excluded for previous use, because that would have introduced a systematic selection bias.

Procedure
From January 2002 to January 2006, 11 waves of private and confidential face-to-face interviews were conducted in school at a frequency of 3 per school year. Interviewers asked all of the smoking-related questions and recorded the responses. Subjects completed psychological measures using paper and pencil, and responses were checked for completeness. When subjects switched schools, an attempt was made to interview them if the new school was within an hour's drive and consented.

For training, the 3 interviewers took turns conducting the scripted interview with mock subjects. One conducted the interview while the others listened. All 3 independently recorded the subjects’ responses and then compared results. This continued until there was 100% agreement.

To minimize subject fatigue and classroom disruption, interviews were designed to be completed in 20 minutes. Demographic data were collected at the first interview, and at each interview the subject's record was updated concerning the types of tobacco used, the duration, frequency, and amount of use and periods of abstinence. Reaction to the first cigarette was recorded at the interview after that event.

The interviewers used techniques that facilitate the accurate recall of dates and events.32,33 A calendar of significant events was created for each tobacco user as a memory aid. Specific dates for smoking events or symptoms were recorded when available. Otherwise, if an event was recalled to have occurred at the beginning of the month, it was recorded as the 7th of the month, the middle as the 15th, and the end of the month as the 25th. Dates were recorded for the first puff, inhalation, whole cigarette, and monthly, weekly, and daily use.

Measures
The main outcome measures were loss of autonomy over nicotine and nicotine dependence. Autonomy is lost when the sequelae of tobacco use, either physical or psychological, present a barrier to quitting.34 Loss of autonomy was assessed using the 10-item Hooked on Nicotine Checklist (HONC; Table 1). Each item has face validity as a measure of diminished autonomy, and the scale has demonstrated a stable single factor structure, good test-retest reliability, concurrent and predictive validity, and excellent internal consistency (Cronbach's {alpha} = .90–.94 in 4 studies of adolescents).34–40 The HONC has been more thoroughly evaluated with adolescents than any other measure of nicotine dependence and is currently in use in 9 languages.41 Subjects were considered to have lost autonomy over nicotine when they experienced their first HONC symptom.


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  		TABLE 1 Interview Questions Used to Assess a Loss of Autonomy and a Diagnosis of Tobacco Dependence According to the ICD-1042

 
To establish a diagnosis of tobacco dependence according to the criteria of the International Classification of Diseases, Tenth Revision (ICD-10),42 we created a 22-item instrument that subsumed the 10 items of the HONC (Table 1). Three of the ICD-10 criteria had to be met to establish a diagnosis. The ICD-10 was chosen over the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition43 because its construct validity has been demonstrated in an adolescent population.44 Dates were recorded for the onset of lost autonomy and ICD-10- defined dependence.

Table 2 lists the 45 predictor variables that evaluated gender (1 measure), reactions to the first inhaled cigarette (4 measures), personality (11 measures), attitudes and beliefs (5 measures), social environment (11 measures), and involvement with family and community (13 measures). As indicated by the references in the table, multi-item scales validated in studies of substance use were used to measure many factors. To keep interviews under 20 minutes, some scales were shortened slightly by dropping items that seemed to duplicate others. The final survey instrument is available from the corresponding author. The items assessing reactions to the first inhalation were retained from the DANDY-1 study, where they predicted the loss of autonomy.30 As a measure of remote exposure to tobacco advertising, subjects were shown the same advertisement used in 1991 to demonstrate that Joe Camel targeted children.45 The brand name and all of the smoking-related objects or text in the ad were masked. Subjects were asked (1) if they had seen Joe Camel before, (2) to identify the product advertised (cigarettes), and (3) to identify the brand name (Camel).


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  		TABLE 2 Internal Consistency of Scales and Bivariate Analyses of the Relationships Between All of the Predictor Variables and Outcome Measures

 
Because of time constraints, one third of the independent variables were assessed at each of the first 3 waves of interviews. Data concerning tobacco use and the dependent variables of autonomy and dependence were collected at all 11 waves.

Data Analysis
Because some of the personality scales had been shortened from their original forms, we began by evaluating the reliability of the shortened scales using Cronbach's {alpha} coefficient and the entire sample of 1246 subjects (Table 2). Missing data on the personality scales were imputed, but missing data for the outcome measures were treated as missing. The performance of the variables as predictors of smoking was evaluated by examining their ability to predict puffing on a cigarette among baseline never smokers. The SAS program (SAS Institute, Cary, NC) was used for these analyses.46

Youths may differ in their susceptibility to dependence or lost autonomy because they persist with smoking for different lengths of time. Because the length of exposure and follow-up varied, stepwise Cox proportional-hazards analyses were performed in Stata (Stata Corp, College Station, TX).47 Half of young smokers do not inhale from their first cigarette.25 Because we were interested in how the first reaction to nicotine influences the development of dependence, the date of the first inhalation was used as the start date for the Cox analyses. One subject who used chewing tobacco before inhaling was excluded from the proportional-hazards analyses because the first inhalation was not the first exposure to nicotine.

All 45 of the variables in Table 2 were of interest as potential predictors of dependence and lost autonomy. Because gender had been identified as a risk factor for the early onset of dependence,48,49 it was forced into all of the models. The sample for this analysis was the subset of subjects who had ever inhaled. With the recent sharp decline in the prevalence of adolescent smoking,50 only half as many youth inhaled as anticipated (n = 217), producing a sample too small to allow all 45 variables to be included in a single analysis. The {chi}2 and t tests were used to identify factors associated with a loss of autonomy (reporting any HONC symptom) at a P value of ≤.25 at the bivariate level, and these were entered as independent variables in a stepwise Cox regression, controlling for gender and clustering by city, with loss of autonomy as the dependent variable. We did not correct for clustering by school, because subjects typically changed schools 3 times between the 6th and 10th grades. A P value of <.05 was used as the test of significance. Continuous factors were divided by their SDs to facilitate the interpretation of hazard ratios (HRs).

Smokers were censored (considered to be no longer at risk and, therefore, removed from the analysis) at the earlier of 2 dates: the 30th day after they smoked their final cigarette or the date of their last interview. Subjects who returned to tobacco use after a long abstinence were conservatively considered to be at continued risk until 30 days after the final cigarette. These analyses were repeated with factors that were associated with ICD-10 dependence at a P value of ≤.25 at the bivariate level as the independent variables and the onset of dependence as the outcome.

To generate Kaplan-Meier survival curves, the above procedure was repeated using time to the first HONC symptom or time to the fulfillment of 3 ICD-10 criteria as the outcome. All of the variables that were significant at the .20 level in the bivariate analyses described above were entered in a stepwise regression, controlling for gender and clustering by city.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Demographics
Of a population of 1808 6th-graders, 68.9% (1246) enrolled in the study. Of these, 77.8% (970) were retained through 11 waves of data collection. The reason for leaving was recorded for 208 of the 276 dropouts; among these, 73% moved to another school. The sample was 51.9% female, with a mean age of 12.2 years (range: 11–14 years) at baseline. Subjects identified themselves as non-Hispanic white (70.2%), Hispanic (18.4%), black (5.0%), Asian (3.7%), and Native American (2.7%).

Tobacco Use
Table 3 summarizes tobacco use history at the first wave of data collection (baseline), the third wave (~9–12 months later, when the acquisition of independent variable data was completed), and cumulatively over the length of participation in the study. Only 1.1% of subjects were current users (past 30 days) at baseline.


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  		TABLE 3 Self-reported Tobacco Use

 
Performance of Measures
Table 2 provides the {alpha} coefficients for each scale (range: .55–.91), as well as the item's or scale's performance in bivariate analyses, as predictors of ever puffing on a cigarette among those who had never used tobacco at the first wave and as predictors of the loss of autonomy or dependence among subjects who inhaled from a cigarette. Bivariate analyses using the {chi}2 and t test, as appropriate, and a Bonferroni corrected P value of <.0012,51 demonstrated that all of the factors listed in Table 2 were associated with "having puffed on a cigarette" among baseline never smokers except gender, sports participation, religiosity, and familiarity with Joe Camel. Twenty six of the variables met the criterion of predicting loss of autonomy among inhalers at a P value of ≤.25, whereas 25 met the same criterion as predictors of ICD-10 dependence.

Loss of Autonomy
Of the 217 subjects who reported inhaling on a cigarette, 58.5% (127) lost autonomy. Feeling relaxed when first inhaling (HR: 3.26) and depressed mood (HR: 1.29 per SD) were significant risk factors for the development of lost autonomy, whereas involvement in extracurricular activities (HR: 0.50), female gender (HR: 0.77), and distractibility (HR: 0.92 per SD) were the significant protective factors (Table 4). Bivariate analysis revealed that 28.7% of first-time inhalers experienced relaxation, and of these, 90.7% subsequently experienced a loss of autonomy as compared with 42.5% of those who did not share this experience. Figure 1 shows survival to the onset of lost autonomy among subjects who did and did not experience relaxation their first time inhaling, controlling for all of the other significant predictors, gender, and clustering by city.


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  		TABLE 4 Cox Regression Analysis Models for the Loss of Autonomy and ICD-10 Dependence Among 217 Inhalers, Adjusted for Gender and All Significant Variables

 

Figure 1
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  		FIGURE 1 Kaplan-Meier survivor function to the loss of autonomy for subjects who did (n = 62) and did not (n = 155) feel relaxed in response to their first time inhaling (P < .001). The y-axis represents the proportion of inhalers that retained full autonomy; the x-axis represents years since first inhalation.

 
Predictors of Dependence
Of the 217 subjects who reported inhaling on a cigarette, 38.2% (83) developed ICD-10 dependence. A relaxed first reaction (HR: 2.43), having seen Joe Camel (HR: 2.19), novelty seeking (HR: 1.56 per SD), and depressed mood (HR: 1.17 per SD) were significant risk factors for the development of ICD-10 nicotine dependence, whereas impulsiveness (HR: 0.60 per SD) and a close relationship with the mother (HR: 0.68) were protective (Table 4). Girls showed a nonsignificant trend in the direction of increased risk (HR: 1.47; P = .065). By the end of follow-up, dependence had developed in 66.7% of subjects who had a relaxed first reaction compared with 28.7% of subjects who did not. Figure 2 shows survival to the onset of dependence among subjects who did and did not experience relaxation their first time inhaling, controlling for all of the other significant predictors, gender, and clustering by city.


Figure 2
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  		FIGURE 2 Kaplan-Meier survivor function to the onset of ICD-10 dependence for subjects who did (n = 62) and did not (n = 155) feel relaxed in response to their first time inhaling from a cigarette (P < .01). The x-axis represents years since the first inhalation.

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
CONCLUSIONS
 REFERENCES
 
Many factors increase the risk that a youth will expose his or her brain to nicotine but do not influence whether that exposure will lead to dependence. We identified 2 factors that increased the risk of the loss of autonomy: experiencing relaxation the first time inhaling from a cigarette and depressed mood. The onset of dependence was predicted by relaxation, familiarity with Joe Camel, novelty seeking, and depressed mood. Of 45 factors studied, only relaxation with the first cigarette and depressed mood remained significant risk factors for the development of both loss of autonomy and ICD-10 dependence when controlled for all of the other factors. Relaxation was the strongest predictor of both. Among inhalers, 29% (comparable to 22% in the DANDY-1 study30) experienced a relaxing sensation on first exposure, and of these, a remarkable 91% had lost autonomy and 67% had progressed to full ICD-10 tobacco dependence by the end of follow-up. Recall bias is an implausible explanation for these findings in this prospective study.

Pleasant initial reactions to nicotine predict continued use.25,26,28,29 We extend this literature by demonstrating that relaxation with the first inhalation predicts dependence even when controlled for trait anxiety and dozens of other personality, environmental, social, and attitudinal factors.2

Because the relaxing effect of nicotine is the primary reason given by both adolescents and adults for smoking,52–60 relaxation may act as a positive reinforcer motivating continued use and thereby increasing the risk of dependence. Cravings might represent the desire to repeat a pleasurable drug-mediated experience. We do not currently understand exactly what youth mean when they report relaxation, and it would seem that this is a ripe topic for future research.

Physiologic differences may underlie differences in the subjective response to the first dose of nicotine. The sensitization-homeostasis theory postulates that dependence results from neurophysiological processes set in motion with the first inhalation.61 According to the theory, nicotine's key action is the suppression of neural pathways that generate craving. This triggers homeostatic adaptations that generate craving autonomously when nicotine is absent. The individual is compelled to smoke to relieve the craving, representing a loss of autonomy over tobacco. In this model, craving occurs independent of any positive reinforcement obtained from nicotine. The suppression of neural craving pathways is experienced as relaxation, and the experience of relaxation with the first cigarette might be a window on this process. If so, symptoms of dependence might be expected after the first few cigarettes. In the DANDY-1 study, youths reported symptoms of dependence after smoking only a few cigarettes,1 and this is supported by the DANDY-2 study and 2 large independent prospective studies.62,63

Sensitivity to nicotine in the form of toxic symptoms from the first cigarette, such as nausea, has predicted future use in some studies but not others.25,26,28,29,64,65 In the DANDY-1 study, nausea predicted the loss of autonomy,30 but this was not replicated in the current study.

Our finding that a novelty-seeking personality increases the risk of dependence is consistent with previous studies. People who score high on novelty seeking are at increased risk for initiating smoking12,66–69 and for developing higher levels of nicotine dependence as measured by the Fagerström scales.68,69 Among adolescents, higher novelty seeking scores correlate with greater receptivity to cigarette advertising, which, in turn, increases the risk of heavier smoking.70

By portraying cool and attractive models, cigarette advertising implies that youths can bestow these attributes on themselves by smoking.71,72 Exposure to cigarette advertising is a well-established cause of smoking, roughly doubling the risk.73,74 The current study demonstrates that exposure to cigarette advertising markedly increases the risk of dependence among youths who have inhaled. Advertising may provide the psychological motivation to continue use until autonomy is lost and dependence follows. The Joe Camel campaign was discontinued in August of 1997 as our subjects entered 2nd grade,75 suggesting that the deleterious effects of cigarette advertising persist long after the exposure.

The co-occurrence of depression and smoking is well known.3,7,13,14,76,79 Current smoking predicts the onset of depression,7,13,77,79–81 but depressive symptoms have not always predicted future smoking13,77,79–81 or the progression to nicotine dependence and daily smoking in adult smokers.13,76 Smokers with a history of depression are reported to suffer more severe nicotine withdrawal symptoms and less success with cessation.82,83 In the current study, depressed mood was associated with increased risk of lost autonomy and dependence. Twin studies provide evidence that the bidirectional relationship between smoking and depression results "solely from genes that predispose to both conditions."77 Our results in regard to depression could be confounded by unmeasured conditions, such as externalizing behaviors.

Distractibility and impulsiveness are 2 symptoms of attention-deficit/hyperactivity disorder (ADHD). Youths with ADHD are at increased risk for smoking.84 ADHD symptoms combine with novelty seeking to raise the likelihood of starting to smoke.85 Smokers who experience symptoms of hyperactivity/impulsiveness during withdrawal are more likely to relapse.86 In the bivariate analysis, impulsiveness was associated with an increased risk of both lost autonomy and dependence. Paradoxically, when controlled for other factors, impulsiveness decreased the risk of dependence (HR: 0.60), and distractibility decreased the risk of lost autonomy (HR: 0.92). Adolescents who take stimulant medications for ADHD are less likely to escalate smoking.87 The protective effect of distractibility and impulsiveness might reflect confounding by the use of ADHD medications. We did not use diagnostic criteria for ADHD or inquire about ADHD medications.

In the current study, girls were at decreased risk of losing autonomy but had a nonsignificant tendency toward increased risk of dependence (HR: 1.47; 95% confidence interval [CI]: 0.98–2.20). Plummeting rates of teen smoking cut the power of our gender analyses. In a Canadian study, girls developed early milestones of dependence faster than boys, but this effect disappeared over time.88 Girls developed lost autonomy much faster than boys in the DANDY-1 study, but that study did not use survival analyses.48 Larger studies with survival analyses may be required to determine the role of gender.

Strengths of this study are the use of 2 established outcome measures, 1 of which has undergone extensive validation in the adolescent population (the HONC); the large number of risk factors assessed; the use of validated multi-item scales to measure many factors; the use of interviews to collect data; 11 waves of prospective data collection; the closely spaced intervals of data collection; the 4-year follow-up; the use of actual dates for events rather than the date of data collection; and the ethnically mixed population.

Limitations include a nonprobability sample that may not be representative of other populations; first reactions and dependence are subjective; all of the data were obtained through self-report; there may be risk factors for dependence that were not measured; we did not consider potential genetic risk factors; we did not consider the use of alcohol or other drugs; and the data may not describe individuals who begin smoking after adolescence. For some subjects, the assessment of predictor variables may have postdated the onset of lost autonomy or dependence, making this a prospective/retrospective study. This might have introduced bias if our psychosocial measures changed over time. By definition, personality traits are stable. Our analyses (data not shown) demonstrated stability in these measures across 3 years, making it unlikely that the outcome was affected by the assessment of personality variables after the onset of smoking in some cases.


   CONCLUSIONS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
REFERENCES
 
The most important factor that drives the transition from inhalation to dependence is whether the first inhalation produces a relaxing sensation. The subjective experience of relaxation in response to the first dose of nicotine represents a promising phenotype for future studies of the heritability of nicotine dependence.

Cigarette marketing causes youths to experiment with tobacco.73,74 Our data indicate that it is also the most important psychosocial or environmental factor driving the progression from the first exposure to dependence in youths, more important than smoking by peers or parents. A ban on tobacco marketing, as recommended by the World Health Organization, seems likely, therefore, to help prevent not only experimentation with tobacco but the progression to dependence as well.89


   ACKNOWLEDGMENTS
 
This study was funded by National Institute on Drug Abuse grant RO1 DA14666 ("the Transition to Nicotine Dependence").


   FOOTNOTES
 
Accepted Mar 16, 2007.

Address correspondence to Joseph R. DiFranza, MD, Department of Family Medicine and Community Health, University of Massachusetts Medical School, 55 Lake Ave, Worcester, MA 01655. E-mail: difranzj{at}ummhc.org

The authors have indicated they have no financial relationships relevant to this article to disclose.

Dr DiFranza had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis; Drs DiFranza, Fletcher, Pbert, O'Loughlin, McNeill, and Ockene and Ms Savageau participated in designing the study and data analysis; Ms Friedman, Ms Hazelton, Ms Wood, and Ms Dussault collected the data; Dr Wellman participated in the data analysis; Dr DiFranza drafted the article; and all of the authors provided their input and approved the final draft.


   REFERENCES
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 CONCLUSIONS
 REFERENCES
 

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