Journal of Pediatric Psychology, Vol. 27, No. 2, 2002, pp. 145-154
© 2002 Society of Pediatric Psychology
Interacting Effects of Depression and Tobacco Advertising Receptivity on Adolescent Smoking
1 Georgetown University Medical Center, 2 University of Pennsylvania School of Medicine
All correspondence should be sent to Kenneth P. Tercyak, Lombardi Cancer Center, Georgetown University Medical Center, 2233 Wisconsin Avenue, NW, Suite 317, Washington, District of Columbia 20007-4104. E-mail: tercyakk{at}gunet.georgetown.edu .
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Abstract |
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Objective: To evaluate the independent effects of exposure to others who smoke and receptivity to tobacco advertising on adolescent smoking practices and the moderating influence of depression on these relationships.
Methods: Participants were 1,123 high school freshmen who completed a self-report survey as part of a longitudinal investigation of the biobehavioral predictors of adolescent smoking adoption. Sixty percent of freshmen reported that they were never smokers (i.e., never tried or experimented with smoking, even a few puffs), and 40% reported being ever smokers (i.e., ever smoked at least a partial or whole cigarette).
Results: In logistic regression models, the adjusted likelihood of ever smoking was greater for students reporting exposure to peer smoking. Further, a significant interaction was detected between receptivity to tobacco advertising and depression; specifically, adolescents with a high receptivity to tobacco advertising and clinically significant depressive symptoms were more likely to smoke than adolescents without these symptoms.
Conclusions: Our data support the hypothesis that adolescents with both high advertising receptivity and depressed moods are most vulnerable to experiment with smoking. Tailoring prevention and intervention efforts to encompass tobacco advertising's effects and the role of depression could lead to a reduction in youth smoking.
Key words: adolescents; depression; tobacco advertising; psychological distress; smoking.
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Introduction |
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Tobacco use is the leading preventable cause of death in the United States (McGinnis & Foege, 1993
).
Even so, growing numbers of adolescents experiment with smoking, and many will
develop a lifelong dependence on nicotine
(Lynch & Bonnie, 1994).
Recent studies indicate that as many as 36% of adolescents are current smokers
(Kann et al., 1998). As youth
smoking often persists into adulthood
(Chassin, Presson, Sherman, & Edwards,
1990; USDHHS,
1994), an estimated 5 million youngsters will eventually die
prematurely from smoking-related illnesses, at an estimated $200 billion in
future health care costs (CDC,
1996).
Why so many adolescents start and continue to smoke despite the associated
risks remains an important public health question. At present, research
suggests that several social and psychological factors significantly increase
the odds that an adolescent will become a smoker. These include the number of
family members who smoke, the number of smoking friends, positive attitudes
and beliefs about smoking (which can be derived from cigarette advertising),
and psychopathology (see Mayhew, Flay,
& Mott, 2000, for review). Deepening our understanding of
these factors, and how they operate independently and in conjunction with one
another, is important to guide adolescent smoking prevention and intervention
programs. Along with biological bases of smoking, these social and
psychological factors are key elements of the biobehavioral model of nicotine
addition and tobacco-related cancers—the predominant framework for
conducting cancer control research (Hiatt
& Rimer, 1999).
Among the most influential social factors is exposure to family members or
peers who smoke (USDHHS,
1994). Compared to adolescents without family members and peers
who are smokers, those who do have an 89% increase in their smoking
susceptibility (Evans, Farkas, Gilpin,
Berry, & Pierce, 1995), and both family and peer smoking are
related to smoking onset (Mayhew et al.,
2000). Though it is commonly thought that the relative influence
of smoking among family members compared to that of peers lessens over time,
longitudinal studies suggest that both remain strong predictors
(Chassin, Presson, Sherman, Montello, &
McGrew, 1986; Wang, Fitzhugh,
Westerfield, & Eddy, 1995). One explanation for this finding
is that family and peer smoking increase smoking acceptability and cigarette
availability (Flay, 1993),
laying a foundation for the adoption of regular smoking.
In addition to risks associated with exposure to family and peer smoking,
promotional advertisement by cigarette manufacturers strongly influences
teenage smoking practices (Lynch &
Bonnie, 1994). Studies have shown that adolescents who frequently
encounter tobacco advertisements are more likely to smoke than those who do
not (Botvin, Goldberg, Botvin, &
Dusenbury, 1993). Encountering cigarette ads, along with attending
to and internalizing their messages, can also influence adolescent receptivity
to such products, thereby increasing their smoking
(Pierce, Choi, Gilpin, Farkas, &
Berry, 1998). Adolescents who are receptive to cigarette
promotional items can be up to three times more likely to progress to greater
levels of smoking than unreceptive adolescents
(Sargent et al., 2000). Pierce
and colleagues (1998) estimate
that over 700,000 adolescents who experiment with smoking each year in the
United States do so as a result of tobacco industry promotional activities,
further underscoring the important influence that tobacco advertising can have
on shaping adolescent smoking behaviors.
Along with social factors, psychological distress has also been associated
with adolescent smoking. Specifically, depression has been linked to
adolescent smoking behavior (Brown,
Lewinsohn, Seeley, & Wagner, 1996;
Covey & Tam, 1990;
Patton et al., 1996).
Depression has been shown to be a predictor of smoking initiation
(Escobedo, Kirch, & Anda,
1996) and is associated with nicotine dependence in adolescents
(Kassel, 2000). Kandel and
Davies (1986) found that
current and lifetime smoking were significantly higher in young adults (ages
24 to 25 years old) who had elevated depressive symptoms as adolescents (ages
15 to 16 years old), suggesting that depression may make an individual
vulnerable to initiating smoking. Nicotine contained in cigarettes is a known
psychostimulant and may induce feelings of euphoria and relaxation, which
could ameliorate depressive symptoms (Anda
et al., 1990). Thus, it is possible that dysphoric adolescents who
experiment with smoking continue to do so to self-medicate their depression
(Glass, 1990).
In contrast to these findings, recent prospective studies have failed to
replicate previous results suggesting depression promotes smoking adoption
(Choi, Patten, Gillin, Kaplan, &
Pierce, 1997; Goodman &
Capitman, 2000). Instead, they showed the reverse; that is,
smoking could be responsible for depression. These contradictory findings
leave open the possibility that the relationship between depression and
smoking may be complex. Perhaps depressive symptoms place some adolescents at
greater risk for smoking than others. Patton et al.
(1996) found that depression
predicted smoking experimentation, though only in the context of peer smoking.
Psychological distress may make adolescents more susceptible to the influence
of smokers in their social environments. Evidence such as this suggests a
greater need to explore interaction effects among key risk factors to
understand their influence on adolescent smoking outcomes.
In one of the few studies that assessed an interaction between the
influence of exposure to family and peer smoking and receptivity to tobacco
advertising on adolescent smoking practices, Evans and colleagues
(1995) reported on
susceptibility to smoking in a large sample (N = 3,536) of adolescent
never smokers. They found that the chance of being a smoker due to exposure to
family or peer smoking was less than that of the chance of being a smoker due
to receptivity to tobacco marketing. Though the authors tested for possible
interactions, none was found. However, the contribution of psychological
distress, such as depression, was not reported, leaving questions about its
interaction effects unanswered. The sadness, negative self-images, and social
withdrawal often associated with depression
(King & Noshpitz, 1991)
may make some adolescents more vulnerable to the effects of tobacco
advertising, which often portrays smoking as pleasurable, relaxing in social
situations, and offering a key to social success
(Lynch & Bonnie,
1994).
Guided by the biobehavioral model of nicotine addiction
(Hiatt & Rimer, 1999), and
in light of the gap in our knowledge about the interrelationships among social
factors, psychological distress, and adolescent smoking, the goal of this
study was to test the hypothesis that the effects of exposure to others who
smoke and tobacco advertising receptivity on youth smoking practices would be
moderated by depression levels. Specifically, we expected that depression
would result in a greater proportion of adolescents who have ever smoked. In
addition, we examined brand-specific cigarette advertising.
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Method |
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Participants
Participants included 1,123 ninth grade students (48% male, 52% female) who were enrolled in five public high schools in northern Virginia. These adolescents constitute a cohort who are being followed for 4 years (through the end of twelfth grade) to evaluate biobehavioral predictors of adolescent smoking adoption and included the collection of genetic data via buccal swab. The racial/ethnic distribution of the sample was as follows: 63% Caucasian, 12% Hispanic, 11% Asian, 8% African American, and 6% of other (e.g., Middle Eastern) descent. In terms of family education level, 18% of respondents' parents attained at least a high school education, 20% completed some college, and 62% were college graduates. These demographics are similar to the state county's profile (U.S. Census Bureau, 2001
).
The percentage of all high school students at each school who were eligible
for a free or reduced price lunch program (a proxy indicator of economic need)
ranged from 6% to 39% (median = 19%)
(Virginia Department of Education,
2001), though the county as a whole has a relatively high standard
of economic prosperity (U.S. Census
Bureau, 2001). Other data on student-family economic status were
not available.
Students were considered to be ineligible to participate in this study if they had a special classroom placement (i.e., severe learning disability and/or English as a second language) (11%), which might preclude valid survey administration.
Eligible participants were identified through class rosters at the
beginning of ninth grade. Based on the above exclusionary criteria, 89% (2,120
out of 2,393) of the total student body was eligible to participate. Project
information packets, including an explanatory cover letter from the school
principal, consent forms, and a brief demographic/response form were mailed to
parents/guardians of all eligible ninth graders. Seventy-two percent (1,533
out of 2,120) of the parents/guardians provided a definitive response
regarding their adolescent's permission to participate and 28% (587) did not
reply: 75% (1,151 out of 1,533) provided consent and 25% (382) declined to
have their adolescent participate. Compared to parents who consented to their
teenagers' participation, parents who declined were over two times more likely
to be Caucasian with a lower level of education
(Audrain, Tercyak, Goldman, & Bush, in
submission). Eligibility required parental consent and adolescent
assent (administrative approval of the study protocol was granted by the
university's institutional review board). Of the 1,151 students with parental
permission to participate, 15 declined (1%) and 13 (1%) were unavailable on
survey administration days due to school absence.
Survey Administration Procedures
Data were collected on-site during health and physical education classes,
which are required courses for all ninth graders. During each class period, a
member of the staff explained the purpose of the project and identified
adolescents with parental consent to participate. Eligible participants were
provided with two assent forms (one to read, sign, and return; one to keep for
their records). After the signed assent forms were collected, participants
received a survey. Subject identification numbers (instead of student names)
were used on all study materials to ensure confidentiality. After the surveys
were distributed, a member of the research team read aloud a set of
instructions, emphasized confidentiality to promote honest responding, and
encouraged questions if survey items were unclear; surveys were usually
self-administered within 30 minutes. All volunteers received $5 gift
certificates to media stores to acknowledge their time and participation in
this study.
Typically, three teams of two project staff per classroom surveyed four to six classes over a 2-day period. To minimize missing data, make-up days were scheduled for those adolescents who were absent during the regular survey administration. Classroom teachers and school administrative personnel did not participate in the survey portion of the research, nor were they permitted to view participants' responses. Students without parental consent completed classroom assignments.
Measures: Dependent and Predictor Variables
Smoking Practices. Adolescent smoking practices were assessed by a
series of standard epidemiological questions regarding tobacco use such as,
"Have you ever tried or experimented with cigarette smoking, even a few
puffs?" and "Have you smoked a cigarette in the past 30
days?" (Kann et al.,
1998). For the purposes of our data analyses, a two-level smoking
variable was created: (1) never smoked = never tried or experimented with
smoking, even a few puffs and (2) ever smoked = ever smoked at least a partial
or whole cigarette. As the group of ever smokers potentially included students
with a range of smoking practices, we further identified a subset of students
who were current smokers (i.e., smoked cigarettes on 
1 of the past 30
days) (Kann et al., 1998).
Demographics. The demographic factors assessed during the baseline survey included student age, gender, and race/ethnicity.
Exposure to Environmental Smoking. Based on prior work
(Choi, Pierce, Gilpin, Farkas, & Berry,
1997), an environmental smoking exposure variable was created.
These items ask adolescents if anyone living in their household smokes, about
the smoking status of their parents, siblings, best friend, other four best
male friends, and other four best female friends. Exposure was defined by four
categories: minimal (no exposure from family or peers), low (family exposure
only), moderate (exposure from peers only), and high (exposure from both
family and peers).
Depression. The Center for Epidemiologic Studies-Depression Scale
(CES-D) is a 20-item self-report measure of depressive symptoms
(Radloff, 1977). Items on the
CES-D are rated along a 4-point Likert scale to indicate how frequently in the
past week each symptom occurred (0 = rarely or none of the time, 3 = most of
the time); scores range from 0 to 60, and higher scores indicate a greater
degree of depressive symptoms. In our study sample, the internal consistency
of the CES-D was adequate (Cronbach's coefficient 
=.87). Prior
research with adolescent samples suggests that gender- and age-appropriate
dichotomous cutoff scores can be used to distinguished those with clinically
significant levels of depressive symptoms (> 24 for females, > 22 for
males) from those without (Roberts,
Lewinsohn, & Seeley, 1991).
Receptivity to Tobacco Advertising. The influence of cigarette
promotional products (minimal, low, moderate, high) was measured using a
standardized scale developed and validated by Pierce and colleagues
(1998). The five-item scale
assessed the purchase, receipt, and use of tobacco promotional items (e.g.,
t-shirt, lighter, or baseball cap that advertises a tobacco brand or was
distributed by a tobacco company), as well as recall of brands advertised most
often, brands of favorite ads, and brands of the ads that attracted the most
attention (resulting in brand-specific information). Participants who could
not name a cigarette brand and who had never received or were not willing to
use a promotional item were classified as having "minimal"
receptivity. Those who could name an often-advertised cigarette brand but did
not have a favorite advertisement were labeled as having "low"
receptivity, whereas those who also had a favorite advertisement were
classified as having "moderate" receptivity. Finally, those who
were classified as having "high" receptivity reported that they
possessed or were willing to use a tobacco industry promotional item.
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Results |
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Smoking Practices. Among the 1,123 participants in this study, a total of 676 (60%) were never smokers and 443 (40%) were ever smokers; 4 students (< 1%) did not respond to enough survey items for their smoking practices to be determined. Among those students who were ever smokers, 127 (29%) were also current smokers. This indicates that the majority of ever smokers in this sample were not currently smoking cigarettes and suggested to us that our primary data analysis should focus on differences between ever and never smokers. As this sample was composed of high school freshman, these differences are meaningful.
Bivariate Analyses
Bivariate analyses tested possible differences between never smokers and
ever smokers based on demographic and other key factors
(Table I). The following is a
description of these results.
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Demographics. Chi-square tests suggested that smoking practices were not independent of gender and race/ethnicity. The group of ever smokers tended to be composed of a higher percentage of male students and students from mostly non-Caucasian backgrounds.
Exposure to Environmental Smoking. Among all respondents, 36% had no exposure to either family or peer smoking (minimal exposure), 10% were exposed to family smoking only (low exposure), 34% were exposed to peer smoking only (moderate exposure), and 19% were exposed to both family and peer smoking (high exposure). Compared to the group of never smokers, the group of ever smokers tended to have a higher proportion of adolescents with greater levels (moderate and high) of environmental smoking exposure. As both of the greater levels include the presence of exposure to peer smoking, whereas the lesser levels (minimal and low) do not, exposure to peer smoking appears to be the key risk factor.
Depression. The M (SD) score on the CES-D was 13.7 (9.4). A statistically significant difference was detected by t test on adolescent smoking status, with ever smokers (M = 15.0, SD = 9.6) having higher scores than never smokers (M = 12.9, SD = 8.6, t [869] = -3.64, p =.000). Based on recommended developmental cutoff scores, approximately 13% (n = 70) of male respondents had clinically significant levels of depressive symptoms, as did 14% (n = 83) of females. Adolescents with depressive symptoms had a stronger tendency to fall within the ever smoker than never smoker group.
Receptivity to Tobacco Advertising. Across both groups, 20% of
adolescents had minimal levels of receptivity to tobacco ads, 36% had low
receptivity, 10% had moderate receptivity, and 34% had high receptivity.
Compared to the never smoker group, the ever smoker group was comprised of a
higher percentage of adolescents falling at the upper end of receptivity
(moderate and high; 60% versus 33%) than at the lower end (minimal and low;
40% versus 67%; 
2 [1] = 78.06, p =.000).
Brand-Specific Advertising. Adolescents' recollections of the most
advertised brand of cigarettes (low and moderate receptivity) and their most
favorite brand (moderate receptivity) were analyzed. There was high agreement
among participants with low and moderate receptivity as to the most frequently
advertised brands of cigarettes (2 [6] = 11.61, p
=.07). In decreasing order of frequency, the top five brands (and their
manufacturers) were Marlboro (Philip Morris), Newport (Lorillard), Camel (R.
J. Reynolds), Virginia Slims (Philip Morris), and Kool (Brown and Williamson).
Interestingly, among students with moderate receptivity, the cigarette brand
rated third in overall advertisement frequency (Camel; 11%) was their most
favorite (39%) and attracted the most attention (41%); the next closest
competitor was Marlboro (26% and 21%, respectively).
Multivariate Analyses
Logistic regression analysis was used to identify factors affecting the
likelihood of an adolescent being an ever smoker (outcome). Predictor
variables with significant bivariate relationships (p <.10) with
smoking were considered in the model. The model was tested in steps and
controlled for the main effects of gender (confounder), race/ethnicity
(confounder), smoking exposure (risk factor), depression (risk factor and
effect modifier), and ad receptivity (risk factor) on Step 1. To ease their
interpretability, multilevel variables were dichotomized. The five-level
race/ethnicity variable was tested as Caucasian and other. The four-level
smoking exposure and tobacco advertising receptivity risk factor variables
were dichotomized into minimal/low (low) and moderate/high (high) levels. This
allowed us to control for the impact of the presence of peer smoking (moderate
and high exposure) in the social environment, as well as greater levels of ad
receptivity, on smoking outcomes.
The results of the multivariate analysis are displayed in
Table II. In Step 1, main
effects of gender, environmental smoking exposure, and ad receptivity were
identified (p <.05); a marginally significant main effect of
depression was also found (p =.09). The results did not suggest a
moderating effect of depression on adolescent smoking exposure (Step 2) but
did indicate a moderating effect of depression on the association between
tobacco advertising receptivity and smoking practices (Step 3). Among
adolescents with clinically significant depressive symptoms, 71% of those with
high receptivity to tobacco advertising were ever smokers. This proportion was
contrasted to the 50% of adolescents with high tobacco advertising receptivity
who were ever smokers without the presence of depressive symptoms, and the
contrast was significant (2 [1] = 5.40, p =.02,
Figure 1).
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In a separate model tested among ever smokers only, we examined the influence of these predictors on increasing the likelihood of an adolescent being a current smoker and the results were essentially unchanged. After controlling for the effects of gender and race, exposure to peer smoking (odds ratio [OR] = 0.16, 95% confidence intervals [CI] = 0.07, 0.37, p =.00) and tobacco advertising receptivity (OR = 0.39, 95% CI = 0.24, 0.65, p =.00) were associated significantly with a greater likelihood of an adolescent being a current smoker. However, the Ad Receptivity x Depression interaction term was no longer significant (p =.23).
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Discussion |
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The results of this study confirm that exposure to others who smoke, high receptivity to tobacco advertising, and clinically significant depressive symptoms are all independently associated with smoking among adolescents. This study also suggests that the presence of depressive symptoms does not further increase an adolescent's vulnerability to smoking when smoking occurs among peers or both peers and family members. However, depressive symptoms are significantly related to smoking in the context of high receptivity to tobacco advertising. Specifically, adolescents who have high levels of depressive symptoms and high receptivity to tobacco advertising are more likely to smoke than are their adolescent counterparts without these elevated symptoms.
In examining the smoking practices of our sample, approximately 40% of over
1,000 high school freshmen reported that they had ever tried or experimented
with smoking. This number is somewhat lower than data reported from the 1999
Youth Risk Behavior Surveillance System (YRBSS;
Kann et al., 2000), which
found that the rate of ever smoking among a nationally representative sample
of ninth graders was 62%; YRBSS data for high school students in the District
of Columbia (the closest neighboring region for which YRBSS data are
available) showed a 63% ever smoking rate. Our rate of current smoking (11%,
127 out of 1,119) was also lower than national (28%) and neighboring region
(20%) estimates (Kann et al.,
2000). However, due to the unique demographic profile of the
county school system from which the sample was drawn, these comparisons should
be interpreted with caution.
In terms of demographic factors that promoted cigarette use, male gender
was associated with a higher proportion of ever smokers, as was non-Caucasian
race/ethnicity. Data from nationally representative samples of high school
freshmen indicate a similar trend with respect to gender, but not race
(USDHHS, 1994). Data on the
effect of exposure to peer or both peer and family smoking on adolescent
tobacco use are also consistent with previously published information; that
is, that the risk of being an ever smoker increases when the level of exposure
is higher (Choi et al., 1997;
Pierce, Choi, Gilpin, Farkas, &
Merritt, 1996).
Contrary to our hypothesis, the effect of exposure to other smokers was not
influenced by depressive symptoms. We expected that the presence of clinically
significant depressive symptoms might increase the likelihood of smoking in
the context of exposure to other smokers, but this was not the case. Thus, it
would appear that the vulnerability to ever using tobacco associated with peer
smoking is not further affected by concurrent levels of psychological
distress. One study showed a significant interaction between depression and
peer smoking as a predictor of smoking initiation
(Patton et al., 1996), though
that study used a different method of determining peer smoking status. They
tested separately the effects of whether no peers smoked, some peers smoked,
and most peers smoked. Our goal was to ascertain if different levels of
exposure to smoking would further vary the risks of being an ever smoker,
depending on the depression status of an adolescent, and the answer appears to
be that it does not.
When we asked a similar question regarding receptivity to tobacco
advertising and its relationship to depression, the results were quite
different. Overall, more adolescents with high receptivity to tobacco
advertising were ever smokers compared to those with low receptivity, and
these results were further affected by depression. Specifically, among
participants with clinically significant depression scores, the effects of
tobacco advertising receptivity were heightened. These adolescents may be less
likely to successfully employ active refusal skills when presented with the
opportunity to receive promotional products and are more attracted to the
positive lifestyles portrayed in tobacco ads. Indeed, research with adolescent
substance abusers has shown that those with higher levels of depression tend
to be more submissive and less assertive, which may place them at greater risk
for substance use (Van Hasselt, Null,
Kempton, & Bukstein, 1993). Other work also highlights the
importance of refusal assertion skills in protecting adolescents from smoking
(Sussman et al., 1993). In
light of the negative findings regarding an interaction between tobacco
advertising receptivity and depression among those who have already tried
smoking, further investigations of how these variables may operate at earlier
stages of experimentation are warranted.
Regarding the brand-specific data that we collected, this information
suggests that Camel remains adolescents' most favorite brand and also attracts
the most attention. Despite discontinuing a highly successful Joe Camel ad
campaign several years ago in response to the Master Settlement, this R. J.
Reynolds brand remains strong among youths. Several of the other brands noted
to be among those most frequently advertised to adolescents in this study have
also been identified as youth brands in other investigations
(King, Siegel, Celebucki, & Connolly,
1998), with Camel and Marlboro remaining the most advertised
brands to teenagers (Pierce et al.,
1991). For those involved in monitoring the industry's activities
regarding marketing and promotional advertisements that are appealing to
youth, our data suggests that even tighter controls may need to be
implemented.
The implications of these data for the prevention and management of
adolescent smoking are several. First, it is critically important that
adolescents, particularly those who grow up in house-holds where one or more
smokers are present, receive messages early on in life about the hazards
associated with tobacco use. Second, in terms of tailoring these messages to
adolescents, it is important to take into consideration their current
psychological state. Adolescents with the highest levels of depressive
symptoms seem to be at great risk for experimenting with smoking. To the
extent that their smoking may be associated with an attempt to alleviate their
symptoms of depression, is used as a stress-reducing coping mechanism, or
occurs in response to social influences to smoke, both education and
counseling should be made available to this particularly vulnerable subset of
youths. Third, antitobacco public education campaigns that seek to dispel
myths about the benefits of smoking that are commonly portrayed in tobacco
advertising should incorporate messages about the potential relationship
between depression and smoking, and how cigarette manufacturers may be
exploiting those who are psychologically vulnerable to smoke. Promoting
awareness of industry manipulation has already been shown to be an effective
component of antitobacco advertising campaigns
(Goldman & Glantz,
1998).
Regarding the limitations of this work, the CES-D does not diagnose
clinical depression, and adolescents' self-ratings of their depressive
symptoms were not confirmed by other means (e.g., clinical interview), which
could have further clarified their scores
(Compas, Connor, & Hinden,
1998). As such, the true extent of their depression cannot be
known. Though roughly 13% to 14% of our sample had scores above the suggested
clinical cutoffs on the CES-D, the sample's mean was within normal limits.
Another important limitation of this work is that only adolescents who attend
school were sampled, and the consent rate for the study was 54%. Thus, data
from a substantial number of adolescents were not obtained. Meaningful
differences between school attenders and nonattenders, and study participants
and nonparticipants, may exist, which could affect the generalizability of our
results, so the data should be interpreted with caution. However, our active
consent rate is consistent with those of other school-based adolescent health
studies (Audrain et al., in
submission); this consistency is important because our study
differs in that it is observational and genetic data were collected. The
relatively high level of parent education and resources may also have lowered
the observed smoking rate in our sample, which could further limit the
generalizability of our findings to other communities. Finally, the
cross-sectional nature of this work limited our ability to draw conclusions
about the directional nature of the relationships observed. For example, in
this study we are unable to determine if depression or high receptivity to
tobacco advertising causes smoking or vice versa. Although the
depression-smoking relationship is still controversial, there are data to
suggest that ad receptivity does contribute to smoking
(Pierce et al., 1998;
Sargent et al., 2000). In the
future, prospective follow-ups should be able to answer these questions more
fully.
Overall, these data provide interesting information about adolescent smoking and its social and psychological risk factors. At present, our findings should alert researchers to the possibility of delving further into social risk factors for smoking by exploring their interactions with key psychological variables, such as depression, anxiety, and elements of personality. Improving our understanding of these interactions should also improve our ability to identify those most at risk to become smokers and to develop tailored antitobacco health promotion messages to these groups based on their unique needs.
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Acknowledgments |
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This study was supported by an NIH Transdisciplinary Tobacco Use Research Center grant (P50 CA84718). We thank Caryn Lerman, David Main, Audra Doss, Carlos Espinel, Janet Herrera, Sharon Zack, and Anahita Nikzad for their contributions to this project. We also extend our appreciation to the high school faculty members, administrative personnel, and students involved in this research.
Received January 30, 2001; accepted July 24, 2001
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