Social-Cognitive and School Factors in Lifetime Smoking among Adolescents

Smoking is the most important preventable cause of cancer in several countries (1). In Denmark, about 20% of deaths among adults ages >35 years are due to smoking (2). Smoking often starts in adolescence; in Denmark, 38% of boys and 32% of girls have tried smoking at age 13 years (3). About 80% of adolescents who smoke at age 15 years will continue smoking in adulthood and about 50% of those who smoke when they are adults will still smoke at age 60 years (4, 5). It is therefore important to identify risk factors for smoking or factors associated with smoking status among adolescents.

Several review studies (6, 7) and a dissertation review (8) have shown that social-cognitive factors such as believing that your friends have positive attitudes to smoking and believing that it is difficult to refuse smoking offers are associated with smoking status, and some of these factors have been found to be responsive to school-based smoking prevention programs (9). The attitude, social influence, and self-efficacy (ASE; ref. 10) model describes how cognitive processes influence the intention to smoke, which often leads to actual smoking (Fig. 1). According to this model, the three social-cognitive factors (ASE model) independently influence smoking initiation.

• Attitude is conceptualized as positive and negative evaluations of smoking (such as believing that smoking is bad for your health).

• Social influence is measured in three dimensions: social norms (teachers' and friends' attitude toward smoking), perceived smoking behavior (among parents and friends), and direct pressure, which may overlap and may work in different directions (11).

• Self-efficacy to resist pressure to smoke is defined as an individual's expectations of capability (12) and focus is on social refusal self-efficacy, which, in the context of smoking, is the expected ability to refrain from smoking in social situations. For both smokers and nonsmokers, the measure of self-efficacy is expected to tap into the belief in one's ability to resist group pressure and also tap into the intention to smoke. Persons who have not tried smoking and do not intend to try smoking may still doubt their ability to refuse. Persons who have not tried smoking may also still intend to try it.

Although many studies have suggested the importance of psychologic risk factors for smoking status, only a few have investigated the effect of the environment. Adolescents spend the majority of their time at school and this environment is thus likely to have a large effect on their lives. However, does that mean that you could have a higher risk of becoming a smoker at one school compared to another? Previous studies have shown that the school (13-16), the school class, and the gender group in the school class (17) may play important roles in smoking status. The school environment can be important because adolescents at the same school share attributes such as their physical environment and neighborhood. Adolescents in the same school class furthermore have the same teachers and spend up to 9 years together on school days. Adolescents in the same gender group (boys versus girls) in a school class also often share friends (18). These school factors have been found to be of particular importance in studies in which the population is sampled by school or school class, because persons in the same sampling unit often have more in common than with those in a different unit. This is referred to as a “clustering effect.” When sampling has been done by school, the school factors can be measured at a group level (instead of at the individual level); this way, one can take into account the variability between schools instead of only between adolescents.

It is important to account for psychological risk factors and environmental factors simultaneously, as these may interact or mediate each other (16) and because a clustering effect might distort the effects of individual psychological factors (19). We conducted a large study involving more than 2,900 adolescents representative of the general adolescent population in Denmark to examine the associations between social-cognitive factors and lifetime smoking, taking into account the effects of the school environment.

The study was based on data for the Danish Youth Cohort collected by the Danish National Institute of Public Health in 2004; data collection has been described previously (20). The data used in this study were baseline data (grade 7) from a longitudinal study of adolescents in six counties of Denmark followed up from grades 7 to 9. The mean age of the participants was 13 years. A total of 4,819 of 7,037 eligible pupils (68%) responded with informed consent from their parents, representing almost 9% of the total population of children in grade 7 at public schools in Denmark (n = 56,739; ref. 21). Of the 4,819 adolescents who agreed to participate, 29 were excluded because of nonresponse. In Denmark, the school system is organized around the school class, which is a group of children who have all their school hours together ideally throughout the first 9 years of primary and lower secondary school (22). In this study, adolescents were asked about which class they were in, not at baseline but in a follow-up study. As not all adolescents chose to participate in the follow-up study, information on class was not available for all persons. We decided to exclude all persons for whom information on school class was not available. This decision was made based on the importance of the effect from school class and gender group in school class found in a study by Rasmussen (17). The final population of the study consisted of 2,913 adolescents distributed across 118 schools, 230 classes, and 436 gender groups. There was an average of two classes per school, with an average of 13 pupils per class. In 24 of 230 classes, only one gender was represented.

We were in this study interested in factors associated with lifetime smoking and thus with all types of smoking experiences among adolescents ages 13 years. Ideally, separate analyses should be conducted for several different stages of smoking [e.g., smoking a puff, previous smoking (monthly, weekly, and daily), current monthly smoking, and current regular smoking (weekly and daily)]. The number of persons in these categories were small in the current study (e.g., daily and weekly smokers; n = 59), and to obtain sufficient statistical power, smoking was measured as lifetime smoking, which implies everything from smoking a puff and previous smoking to current daily smoking. The information was based on answers to two questions (Table 1). The first question was on current smoking: “Do you smoke cigarettes?” The second question was on previous smoking: “Which sentence fits you the best? 1. I have stopped smoking, I smoked at least once a day,” etc. Adolescents were considered to be a lifetime smoker if they scored 1 to 5 on the first or second item. Thus, if a person answered “6. No, I do not smoke” in question 1 and “5. I have smoked a total of a couple of cigarettes at the most” in question 2, they would be considered a lifetime smoker. If an answer was missing to one question, the other response was used. If answers were missing to both questions, they were excluded from further analyses.

The social-cognitive factors (Fig. 2) were measured based on items and indexes constructed and examined for their “criterion-related construct validity” in a previous study (20). Three of the indexes [social influence (norms; seven ordinal levels), social influence (pressure; four ordinal levels), and attitude (nine ordinal levels)] had satisfactory validity and were therefore used in the study. Two indexes [self-efficacy to resist pressure to smoke and social influence (behavior)] did not have satisfactory validity and had to be measured from individual items. We used one individual measure of self-efficacy to resist pressure to smoke (five ordinal levels) and three individual measures of social influence [behavior; mother's, father's, and best friend's smoking (each with three nominal values)].

Several demographic and school well-being factors that have been shown to be potential confounders (17, 23) were included in the analyses (Table 2). Family affluence was assessed from three items: “How many cars do you have in your home?” none, one, two, more than two; “Do you have a room to yourself?” no, yes; and “Last year, how many times did you go on vacation with your family?” none, once, twice, more than twice. The item responses were dichotomized and summarized for a total score from 1 to 4. The family affluence scale has been found to be an appropriate proxy for socioeconomic status among adolescents (24-26). Besides the individual factors, three group levels were explored: school, school class, and gender group in the school class.

Multilevel logistic regression models (GLIMMIX procedure, SAS 9.1 statistical package, SAS Institute) were used to estimate the (fixed) effects on an odds ratio (OR) scale of the social-cognitive factors and the (random) effects of school, school class, and gender group in school class. Factors that are included conventionally in multilevel logistic regression are called “fixed effects” to distinguish them from random effects. Like conventional (multivariate) logistic regression models, multilevel logistic regression models relate the log odds of the event (e.g., smoking) to a linear combination of risk factors. Although, in conventional logistic regression, estimates of variables for each level of the factors are of interest, in multilevel logistic regression analysis, levels of selected factors are assumed to be described by a Gaussian distribution and are included in the logistic model as such. We included school, school class, and gender group as nested random effects in the model. This implies that that these factors were modeled in a way that takes into account the clustering between persons within the different structures. As estimates of random variance components are often difficult to interpret, they were converted to median OR (27) and thus translated into an OR scale. Median OR is theoretically the increased median risk resulting from a move to, for example, another school with a higher risk for smoking. It is directly comparable with the OR of individual variables (19). Median OR was computed from the formula (19):

where V_A is the corresponding group-level factor variance and 0.6745 is the 75th percentile of the cumulative standard Gaussian distribution.

To investigate the effects of the group-level factors and the mediating abilities of social-cognitive factors, the ASE model was constructed by examining an increasing portfolio of models. First, models that included only the group-level factors added individually were examined to assess the raw context effects on smoking. Then, each social-cognitive factor was added individually to the model to assess the association with the individual factor. This was repeated in the presence of demographic and school well-being factors as potential confounders. Finally, a model that included all the social-cognitive factors and confounders was used to estimate if the social-cognitive factors had individual effects on smoking status.

In a previous study, we examined the criterion-related construct validity of the social-cognitive indexes and found that some had positive local dependence and differential item functioning (20). Positive local dependence implies that the dependence among certain items is stronger than their relation to the assumed common latent trait; differential item functioning implies that item scores depend not only on the assumed latent trait but also on exogenous variables such as gender and ethnicity (28). The presence of local dependence in the indexes used in the current study means that the OR should be interpreted with caution. The overall association of these indexes with smoking was therefore additionally examined with F tests. The presence of differential item functioning from gender and liking school on attitude and from gender on social influence (norms) was accounted for by including corresponding interaction terms. For each of the continuous predictors, self-efficacy to resist pressure to smoke, social influence (norms), social influence (pressure), and attitude, we tested whether the association with smoking status was linear on a logit scale. Linear trends were seen for social influence (norms) and social influence (pressure), whereas a quadratic term was added for attitude, and a separate estimate for score level 5 was added for self-efficacy to resist pressure to smoke to account for nonlinearity. The three measures of social influence (behavior) were included as categorical variables.

In a subanalysis, we furthermore examined the mutually and confounder adjusted fixed effects of the social-cognitive factors on lifetime smoking while excluding persons who were current weekly or daily smokers (n = 59).

At baseline in 2004, the mean age was 13 years. Slightly more boys (24%) than girls (22%) had tried smoking. Few adolescents were regular smokers: 23% had ever tried smoking, 17% had tried a couple of cigarettes at the most, and 6% had tried more than a couple of cigarettes. The results of descriptive statistics showed that self-efficacy to resist pressure to smoke, social influence (norms), social influence (behavior), social influence (pressure), and attitude were associated with smoking status (Table 3). Of the potential confounders, family structure (living with one parent), not liking school, negative relationships with classmates, and lack of family religiousness among boys appeared to be associated with smoking (Table 2).

The multilevel analyses showed that the social-cognitive factors were significantly associated with smoking status after adjustment for the random effects of school, school class, and gender group in the school class (Table 4; Fig. 3). In addition, we generally observed that the estimated associations became weaker after adjustment for potential confounders and were weakened slightly further after mutual adjustment for all social-cognitive factors. Nevertheless, all social-cognitive factors remained significant in the adjusted models (Table 4). F tests in the final model confirmed that each of the indexes was significantly associated with smoking status.

In the fully adjusted model, self-efficacy to resist pressure to smoke was strongly associated with smoking status [OR, 1.7; 95% confidence interval (95% CI), 1.5-1.9; Table 4]. For social influence (norms), no difference in effect was seen between boys (OR, 1.3; 95% CI, 1.2-1.5) and girls (OR, 1.3; 95% CI, 1.1-1.4). Best friend's smoking (OR, 3.4; 95% CI, 2.5-4.6) and social influence (pressure; OR, 2.1; 95% CI, 1.8-2.4) also both showed strong associations. The effect of attitude was slightly greater among girls than boys (Fig. 3) and varied only slightly with the level of liking school, the middle level showing the strongest effect. The results of the subanalysis examining the mutually and confounder adjusted fixed effects of the social-cognitive factors on lifetime smoking while excluding persons who were current weekly or daily smokers (n = 59) showed only small differences compared with when these persons were included. All social-cognitive factors had a significant effect on lifetime smoking: self-efficacy [OR, 1.6; 95% CI, 1.5-1.8], social influence (norms) same results for boys and girls [OR, 1.2; 95% CI, 1.1-1.4], mother smokes [OR, 1.6; 95% CI, 1.3-2.0], father smokes [OR, 1.3; 95% CI, 1.0-1.6], best friend smokes [OR, 3.1; 95% CI, 2.2-4.2], social influence (pressure) [OR, 2.1; 95% CI, 1.8-2.4] and attitude [OR, 1.5; 95% CI, 1.2-1.8].

We found wide variation in smoking prevalence among schools, classes, and gender groups in the school class. The results of null models showed that the effect of school decreased when school class and gender group in the school class were introduced and that the effect of school class vanished when gender group was introduced. The random effect of school and the effect of gender group in the school class increased when confounders and social-cognitive factors were added to the model (Table 5). The largest random effect in the adjusted model was that of gender group in the school class (median OR, 2.45).

The results of this study show that all the social-cognitive factors examined were significantly associated with lifetime smoking status. The association between self-efficacy to resist pressure to smoke and smoking status suggests that a belief in being able to refrain from smoking is important for whether or not a person smokes, but the direction of the causal pathway should be confirmed in longitudinal studies. Our results are in accordance with those of previous studies, including a high-quality review (8), which found that self-efficacy is associated with smoking status, and a Dutch study of 85 adolescents, which found that this factor makes a unique contribution among the ASE factors (29).

Our results also showed that all three types of social influence were significantly associated with smoking status. The association between social influence (norms) and smoking status suggests that the norms of best friends, friends, and teachers toward smoking are important for smoking status. These results are consistent with those of a review, which supported associations between smoking status and the norms of peers (6). Also, a cross-sectional study (n = 6,274) on social norms showed a strong association between smoking status and adults disapproving of adolescent smoking (30).

We found strong associations between friends' smoking, parental smoking, and smoking status. Previous studies have had diverging results with regard to parental smoking. A large longitudinal study of a cohort of 5,520 families showed that the probability that having two parents who smoked would influence a child to try smoking was 53% (31), but two earlier reviews concluded that, although peer smoking has consistently been found to influence smoking status, the results for parental smoking have been inconsistent (8, 32).

Social influence (pressure) was strongly associated with smoking status, with an estimated doubling of risk per score. This suggests that direct pressure from best friends, friends, and other adolescents may play an important role in lifetime smoking. It should be noted that adolescents might be influenced to smoke by their peers, but they might also select their friends based on their smoking status. A longitudinal study of 20,747 adolescents in the United States, in which structural equation models were used, showed that both peer influence and peer selection were present, peer influence being the most salient (33), but a review of previous qualitative studies in this area concluded that peer selection plays an important role (34).

In accordance with previous studies that found an effect of attitude, we found a significant association between attitude and smoking status. A review pointed out that positive attitude is especially important (8), whereas a Hungarian cross-sectional study of 261 randomly selected adolescents, in which factor analysis was used, found that an antismoking attitude was important (35). We found a positive effect of a positive attitude on smoking status, indicating that considering that smoking is not stupid or bad for the health makes an adolescent more likely to try smoking. The effect of attitude was slightly greater among girls and among pupils at middle levels of liking school. It is possible that there is a stronger concordance between attitude and smoking behavior among girls than boys and that attitude plays a more important role among pupils with a neutral perception of going to school than among those with a positive perception of school.

In summary, the associations found in this study between smoking status and social-cognitive factors reaffirm the place of these factors in the ASE model.

Concerning the group-level effects, the median OR for gender group in the school class, after considering the effect of school and school class, was 2.45, indicating that if an adolescent moves from one randomly chosen gender group to another with a higher risk for smoking, the risk is increased by a median of 2.45 times. The finding that gender group in the school class is the strongest group-level factor suggests that it is a more refined way of measuring a class effect because it takes into account differences between gender groups in smoking prevalence and that in some school classes, for example, most of the boys are smoking, whereas none or few of the girls are smoking or the other way around. Our results on gender group in the school class suggest that the social influence of peers does not operate across the gender boundary. This implies that the girls are influencing each other to smoke and the boys are influencing each other to smoke. This is possibly due to the fact that close friendships are often gender specific in this age group and that it is especially within close friendships adolescents influence and model each other. Previous studies of the role of gender in smoking initiation include a qualitative study with in-depth interviews of 85 adolescents in Northern Ireland, which suggested that girls often link smoking with romance and femininity, whereas boys link smoking with being cool, hard, and masculine (36).

Although the data support was weak, a review reported some gender differences in psychosocial determinants of smoking, for example, that female smoking was associated with self-confidence, rebellion, and social experience, whereas male smoking was associated with social insecurity (37). Our results showed a strong effect of gender group in the school class, even after accounting for individual measures of social influence, suggesting that the social influence might derive from numerous sources simultaneously. The mechanisms underlying the effect of gender group in a school class have not been articulated previously but could, as described in a discussion of theoretical and empirical findings on peer and adolescent smoking (38), be associated with adolescents' decisions to start smoking in order to fit in or to affect their popularity, individuality, status, and thus their own social position in relation to the dynamics of the gender group.

The importance of gender group in the school class also suggests that the group with the highest proximity is the most important for smoking status. Consistent with our findings, previous studies have found that close peer groups are more important than more peripheral (17, 39, 40). A longitudinal study of 6,527 adolescents in the United States showed that school-level smoking was not associated with smoking initiation, whereas peer smoking was (39). A longitudinal study of 2,883 adolescents in Sweden showed that class-related rather than school-related factors were associated with smoking initiation (40). If the three group-level factors are seen from a social learning perspective, they can be incorporated into the ASE model (Fig. 1). The three hierarchical group-level factors could represent three levels of social proximity: the school, with low proximity, defined in social learning theory as the “imposed environment” (41); the school class, with medium proximity; and the gender group in the school class, with the highest proximity, similar to the “selected environment” in social learning theory (41). Further studies are needed to explore the effect of gender group in the school class to identify specific factors that explain this effect.

One of the main advantages of this study is the large, gender-balanced, population-based sample of more than 2,900 adolescents at 118 schools, which were randomly selected from the public school system. Small samples have sometimes been used in studies in this area (29, 35), but the advantage of a larger sample is that it allows use of large statistical models that include many relevant variables. Inclusion of adolescents in six counties meant that those in both rural and urban areas were represented and that the study population was representative of the general population of the same age group with regard to several exogenous variables, such as ethnicity and family structure (42, 43). Another advantage is that we were able to take into account results from a previous validation study that provided evidence of deviations from criterion-related construct validity for the social-cognitive indexes. Items are often collapsed into scales without further psychometric investigation (30), but ignoring these issues can distort results. In addition, because of the hierarchical structure of the data, multilevel analyses could be done with three nested group levels. Instead of measuring gender group in the school class as a group-level effect, one could measure an interaction between school class and gender, but this would not take into account the hierarchical structure of adolescents within the specific school and school class (17). To our knowledge, this is the first study to include group-level factors in multilevel analyses for exploring the ASE model factors. Finally, this study included adjustment for several important confounders that are rarely included, such as liking school, liking classmates, and family structure.

One limitation of the study was that it was based on cross-sectional data, which provide weak evidence for the direction of a cause-effect relation. Despite its cross-sectional design, the results of the study pointed to important associations, which should be explored in longitudinal studies. In this study, we examined lifetime smoking including both adolescents who, for example, smoke daily and who have smoked only a puff. Previous studies have shown that different smoking stages may have different cognitive characteristics (44). Ideally, separate analyses should thus be done for different stages of smoking [e.g., smoking a puff, previous smoking (monthly, weekly, daily), current monthly smoking, and current regular smoking (weekly and daily)], but because this study included adolescents ages 13 years (an age group with few smokers in each of these stages), this would have resulted in lack of sufficient statistical power.

As seen in Table 1, the majority of adolescents who in this study were classified as smokers had smoked a couple of cigarettes at the most and smoking status in this study thus mainly implies experimental smoking. In addition, the number of persons who were current regular smokers was low (n = 59). The results of the subanalysis of the social-cognitive factors on lifetime smoking while excluding persons who were current weekly or daily smokers (n = 59) only showed small differences compared with when including these persons. Thus, we have no indications of the inclusion of current regular smokers distorting the results. The current study is cross-sectional and it may be less complicated to investigate these issues in longitudinal studies because there is more control of the timing of social-cognitive factors and smoking status.

Another potential limitation lies in the co-linearity among the social-cognitive factors. Mutually adjusted analyses estimates individual effects of the social-cognitive factors, but due to the co-linearity the estimates may not be interpreted straightforwardly. We conducted unadjusted, confounder adjusted, and mutually adjusted analyses to clarify the influence of this co-linearity. Finally, selection bias might be a potential problem. The fact that 56% of the invited schools did not participate might have led to selection bias, as the nonparticipating schools might have differed from the other schools, for example, with higher smoking rates; however, we were unable to investigate this hypothesis, as we had no information on the nonparticipating schools. As the study population appeared to be representative of the general population in respect of several variables, however, there was no indication of selection bias.

The public health message of this study with regard to prevention of smoking is that social-cognitive factors if their effect is confirmed in longitudinal studies could be targeted, for example, in school-based programs (suggested by the importance of peers), by teaching social skills (to target self-efficacy to resist pressure to smoke) and facts about smoking (to target attitude), and by involving parents in the program (suggested by the importance of parents' behavior). The results for the school factors suggest that the school class environment and gender are important, but more knowledge is required about the underlying mechanisms. It might be relevant to perform screening and then to target prevention initiatives to, for example, the boys in specific classes, at specific schools.

The results suggest that the individual-level factors (social influence, attitude, and self-efficacy to resist pressure to smoke) are important for smoking status, even when the effect of school, school class, and gender group in the school class is taken into account. Social-cognitive factors constitute a complex web, each influencing the other as well as smoking behavior. The results support use of the ASE model as a theoretical framework but emphasize the importance of viewing individuals in their social context, where school and gender play important roles.

No potential conflicts of interest were disclosed.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

We thank the Danish National Institute of Public Health for giving us access to data.