Introduction
In most Western countries, smoking onset increases most rapidly during adolescence. In 2009, 7% of 11-years-old adolescents in the Netherlands indicated that they had tried smoking during their lifetime. This increased to 45% by the age of 14 and 62% by age 17 (Stivoro,
2009). These smoking rates are similar to those in the UK (National Centre for Social Research,
2010) and the US ((MMWR)
2010). It is important to prevent young adolescents from smoking because people who initiate smoking early in life are more likely to develop a long-enduring smoking habit (e.g., Chassin et al.,
2000). To better prevent the onset of adolescent smoking, increased insight into the exact timing of adolescent smoking and its predictors is necessary. The aim of the present study was to gain insight into the timing of smoking onset and the time-varying effects of refusal self-efficacy, environmental smoking, and smoking-specific parenting throughout mid- or late adolescence.
One way to look at the timing of smoking onset is by means of survival analyses (Willet & Singer,
1991; Willet & Singer,
1993), also called event history analyses (Allison,
1984). Survival analyses encompass a wide variety of statistical methods to analyze occurrence and timing of events, and it offers two main advantages in comparison to traditional analytic methods to examine behavior over time (Willet & Singer,
1993). Particularly, when studying adolescent smoking, most traditional studies aimed at smoking onset ignore the time to when smoking occurs, and do not take into account the censoring of smoking behaviors (Bidstrup et al.,
2009; Grogan et al.,
2009; Lotrean et al.,
2010). Censoring is an important feature of survival-time data. Specifically, the survival times of some respondents are unobserved, for instance, because smoking onset did not take place before the termination of the study, which makes information about the occurrence of smoking onset of these respondents (i.e., respondents with censored data) incomplete. Failure to take this specific feature of survival data into account can produce serious bias in estimates of the distribution of survival time and related quantities. Standard statistical tools do not allow the calculation of the mean duration of episodes when observations are censored (Systema et al.,
1996).
The present study used discrete-time survival analyses (Singer & Willet,
1993; Willet & Singer,
1993) because data were gathered at specific time points and not continuously over time. Discrete-time survival analysis allows for examination of the longitudinal progression of the probability that an event occurs (Muthen & Masyn,
2005); thereby, providing a more accurate insight into whether adolescents start smoking and when (Singer & Willet,
1993; Willet & Singer,
1991; Willet & Singer,
1993). Furthermore, the majority of longitudinal studies measure predictors at one point in time thereby partially overlooking the idea that values of predictors may vary over time, and not permitting the effects of the predictors to fluctuate (Willet & Singer,
1991). Discrete-time survival analysis allows the inclusion of time varying predictors, whose values fluctuate over time. In conclusion, by means of survival analyses a more accurate prediction of smoking onset can be made. As an additional consequence, the use of survival analyses may cause magnitudes of effects to differentiate (i.e. be weaker or stronger in magnitude) from those found in studies using more traditional techniques.
One important predictor that is assumed to vary over time and affects adolescent smoking is refusal self-efficacy (de Vries et al.,
1988; Engels et al.,
1997), which refers to adolescents’ confidence in their ability to stay a non-smoker and the confidence to refuse a cigarette (de Vries et al.,
1988; Engels et al.,
1999). Self-efficacy has been widely used to explain smoking initiation in youths (e.g., Petraitis et al.,
1995). In some longitudinal studies, higher levels of self-efficacy related negatively to smoking onset (e.g., Bidstrup et al.,
2009; Chang et al.,
2006; de Vries et al.,
1995; Grogan et al.,
2009; Lotrean et al.,
2010) but in other studies, self-efficacy did not relate to adolescent smoking onset (e.g., Ayo-Yusuf et al.,
2009). Despite the prospective nature of these studies, only some of these studies took smoking onset at different time points into account (Bidstrup et al.,
2009; Chang et al.,
2006; Lotrean et al.,
2010). Most studies assessed self-efficacy and smoking initiation over a short period (two or three time points) (Bidstrup et al.,
2009; Chang et al.,
2006; Grogan et al.,
2009; Lotrean et al.,
2010). Moreover, some of these studies applied relatively small time intervals (2-year or shorter), limiting the possibility to examine the smoking onset throughout adolescence (Bidstrup et al.,
2009; de Vries et al.,
1995; Grogan et al.,
2009; Lotrean et al.,
2010).
Besides self-efficacy, parental, sibling, and peer smoking are associated with adolescent smoking (e.g., Avenevoli & Merikangas,
2003; Harakeh et al.,
2007; Otten et al.,
2009). Parental smoking status affects the likelihood that adolescents will start smoking and, over time, the development of a more habitual smoking pattern (e.g., Mayhew et al.,
2000; Gilman et al.,
2009). Smoking behavior of an older sibling affects smoking onset of an adolescent (Avenevoli & Merikangas,
2003; Harakeh et al.,
2007), although friends’ smoking is considered to be a stronger predictor of adolescent smoking than sibling smoking (Avenevoli & Merikangas,
2003). Adolescents with smoking friends have been found to be more likely to smoke themselves as compared to adolescents with nonsmoking friends (for a review see Hoffman et al.,
2006; Kobus
2003).
Another parental factor, smoking-specific parenting, has been shown to be important in adolescent smoking behavior (Chassin et al.,
1998; Conrad et al.,
1992). Smoking-specific parenting includes specific strategies aimed at preventing smoking onset by setting rules, transmitting knowledge on smoking, and encouraging antismoking attitudes (i.e., antismoking socialization) (e.g., Engels & Willemsen,
2004; Ennett et al.,
2001; Harakeh et al.,
2005; Jackson & Dickinson,
2003). Earlier research established that smoking-specific parenting practices reduce the odds of adolescents being involved in smoking (e.g., Chassin et al.,
2005; de Leeuw et al.,
2008; de Leeuw et al.,
2010; Harakeh et al.,
2005). Moreover, parents engage in different socializing efforts, such as constructive forms of communication about smoking issues, to influence their adolescent’s decision to smoke. Previous research has found that frequency of communication is associated with adolescent smoking (e.g., positively: Chassin et al.,
1998; Clark et al.,
1999; Jackson & Henriksen,
1997; negatively: Ennett et al.,
2001; Harakeh et al.,
2005). Higher quality of communication was negatively associated with adolescent smoking (e.g., Chassin et al.,
2005; de Leeuw et al.,
2008; de Leeuw et al.,
2010; Harakeh et al.,
2005; Otten et al.,
2007). The divergent findings with respect to frequency and quality of communication could be a reflection of parents’ reaction to the smoking behavior of the adolescent.
Self-efficacy, environmental smoking, and smoking-specific communication are included in some of the most important theories in explaining adolescent health risk behavior (Petraitis et al.,
1995). These theories have suggested that the major influences on adolescent smoking are social environments and psychological factors. Specifically, environmental smoking has been found to affect adolescent smoking through processes of modeling (e.g., Engels et al.,
1999), accordingly with social cognitive theories (Bandura,
1986), and parents exert socializing efforts through constructive forms of communication (Otten et al.,
2007). From a similar theoretical perspective, yet on a more individual level, refusal self-efficacy has been shown to protect children from smoking (e.g., Petraitis et al.,
1995). In addition to the direct effects of self-efficacy, environmental smoking exposure, and smoking-specific parenting on smoking onset, it is likely that smoking behavior is a product of an interplay between individual and environmental factors. Specifically, we expect a weaker role of self-efficacy in children exposed to both peers and parent who smoke (e.g., Bauman et al.,
2001; de Vries et al.,
2003). Environmental smoking and communication about of smoking may affect refusal self-efficacy in a respectively negative and positive way, which in turn may decrease or increase the odds for adolescent smoking. Adolescents of parents who smoke may perceive smoking as relatively normative behavior (Bricker et al.,
2007). As a consequence, these children may be less likely to refuse a cigarette. We also expect a stronger role of self-efficacy in children whose parents engage in smoking-specific parenting (Engels & Willemsen,
2004; Huver et al.,
2006; Otten et al.,
2007). Parents play an important role in encouraging a child’s self-efficacy: children of parents who discuss smoking matters are expected to be more confident in their ability to refuse cigarettes from peers.
The present study
The main objective of the present study was to examine the timing of smoking onset during mid- or late adolescence and the time-varying effects of refusal self-efficacy, parental smoking, sibling smoking, friends and best friend’s smoking, and smoking-specific communication. In addition, we examined how the exposure to environmental smoking (i.e., parental, sibling, and peer smoking) and smoking-specific parenting (i.e., frequency and quality of communication) might alter the relation between self-efficacy and adolescent smoking onset during mid- or late adolescence. This was tested using survival analyses. We expected that lower self-efficacy, smoking behavior of parents, older sibling, peers, and more frequent communication as well as lower quality of communication would be important predictors of the timing of smoking onset. Further, we expected that environmental smoking and smoking-specific communication alter the relationship between self-efficacy and smoking onset.
Discussion
The present study examined the timing of smoking onset during mid- or late adolescence and the role of the time-varying effects of refusal self-efficacy, parental smoking, sibling, friends and best friend’s smoking, and smoking-specific parenting. Survival analyses were used to give insight into whether smoking onset occurred and when (e.g., Singer & Willet,
1993). The majority of longitudinal studies predict smoking by looking at predictors at one point in time, partially ignoring the idea that the effects of certain predictors may change or fluctuate over time (Willet & Singer,
1991). By looking at the particular time-related effects of different predictors, survival analyses are more accurate. Moreover, survival analyses minimize bias, because non-occurrence of smoking is taken into account (censoring). The present study looked at smoking onset in mid- or late adolescence.
Results of the life table approach provided important preliminary information about when smoking onset occurs during mid- or late adolescence by estimating survival and hazard rates. Findings revealed that 51% of all non-smoking respondents at baseline did not start smoking within the study period. To be able to accurately compare these results with national data, also the early initiators need to be taken into account. At age 13–14 (baseline assessment), 153 respondents reported lifetime smoking and were excluded from the analyses. From the respondents that were included in the analyses, 120 respondents started smoking at some point during the study period. So, at the final assessment at age 17–19, in total 273 respondents (63.8%) had some experience with smoking, which is in line with national data on smoking in the Netherlands (Stivoro,
2009). Smoking initiation risks were quite similar throughout mid- and late adolescence (hazard ratio between .16 and .19).
Discrete-time survival analyses were used to assess the relationship between self-efficacy, smoking behavior of parents, sibling, friends’ and best friend and smoking-specific communication, and adolescent smoking onset. An advantage of discrete-time survival analyses is that it takes into account the time-varying predictors, whose values fluctuate over time. We found that during mid- or late adolescence self-efficacy, sibling smoking, and frequency of communication assessed 1 year prior to onset are important predictors of smoking onset.
For self-efficacy, we found that adolescents with high levels of self-efficacy were less likely to start smoking in the following year, even after controlling for environmental smoking and smoking-specific parenting. This is in line with previous longitudinal research (Bidstrup et al.,
2009; Chang et al.,
2006; de Vries et al.,
1995; Grogan et al.,
2009; Lotrean et al.,
2010). In a recent paper (Hiemstra et al.,
2011), we found comparable effects of self-efficacy on adolescent smoking behavior over time. A decrease in self-efficacy over time is associated with smoking progression, even after controlling for parental, sibling, and friends’ smoking behavior.
In addition, we also found that more frequent parental talking about smoking-related issues with their children was associated with an increased risk for children to start smoking. Specifically, frequency of communication about smoking related issues predicted smoking onset 1 year later. This finding might indicate that when adolescents start to experiment with more deviant behavior in general and drift towards deviant peers, parents might react to that by talking more often with their children. Previous cross-sectional studies found similar results of higher frequency of communication (e.g., Ennett et al.,
2001; Harakeh et al.,
2005; Otten et al.,
2007). However, contrary findings were also found (e.g., Chassin et al.,
1998; Clark et al.,
1999; Jackson & Henriksen,
1997). Existing longitudinal studies found no association between frequency of communication and adolescent smoking onset (den Exter Blokland et al.,
2006; Ennett et al.,
2001). It could be that some of the inconsistent results are reflections of interactions between frequency of communication and quality of communication. For instance, it could be that in some studies parents engaged in both high levels of frequency of communication and high levels of quality of communication indeed causing preventive effects. Alternately, other parents could engage in high levels of frequency together with low levels of quality of communication actually increasing the risk for smoking. Another explanation could be that environmental smoking moderates the effects of frequency of communication on adolescent smoking. No previous research has been conducted on the circumstances under which frequency of communication might have positive or aversive effects. Hence, more longitudinal studies should look into this to provide more insight into the circumstances in which frequency could be effective.
In contrast to other studies, no association was found between quality of communication and adolescent smoking onset (e.g., Chassin et al.,
2005; de Leeuw et al.,
2008). An explanation for not finding an association could be that parents only started talking about smoking matters, or changed their way of communicating, after their child had tried smoking (de Leeuw et al.,
2010).
2
Previous research found that smoking behavior of sibling, friends and parents is related to smoking onset (e.g., Avenevoli & Merikangas,
2003; Bauman et al.,
2001; Harakeh, et al.,
2007), however these studies did not involve survival analyses. In the present study, we indeed found support for the relationship between sibling smoking behavior and adolescent smoking onset. An explanation for sibling smoking may be that younger siblings perceive older siblings as important role models, and they are likely to model their behavior (Harakeh et al.,
2007). The effect of friends’ smoking was marginally significant and no association between parental smoking and smoking onset was found. In this study, we looked at the first experience with smoking. Since the first smoking experience is with friends and the survival analyses concentrates at smoking onset at each point in time, this might have caused an absence of the effect of parental smoking. Moreover, samples with adolescents aged 13 or older it has been found that the influence of parental smoking is less important than that of friends’ smoking on smoking onset (e.g., Gilman et al.,
2009). Finally, in contrast to our expectations, no-interaction effects between self-efficacy and quality and frequency of communication, smoking behavior of parents, sibling, and friends were found. Refusal self-efficacy appears to be independent of the frequency and quality of parental communication and parents’, friends’ and sibling smoking.
Strengths, limitations, and implications
This study has several strengths. A longitudinal design was used, and by conducting survival analyses, the timing of smoking onset was taken into account as well as the non-occurrence of an event (censoring). However, some limitations of this study should also be acknowledged. First, adolescents had to report about own smoking behavior and about smoking by their friends’ and best friends. Although previous research has shown that self-report data about smoking (e.g., Dolcini et al.,
2003) and adolescents’ reports about friends’ smoking habits (e.g., Harakeh et al.,
2007) are generally reliable, multi-informant data would have been more complete. Second, by using survival analyses, adolescents with a history of smoking at the first assessment were excluded from the analyses. Early initiators differed from never smokers at the first assessment with respect to self-efficacy, environmental smoking, frequency of communication and quality of communication (Table
1). The mechanisms underlying smoking onset might differ for those who start early in adolescence as compared to those who start in mid- or late adolescence. It is therefore relevant to stress that conclusions of this study can only refer to adolescents who started smoking in mid- or late adolescence. Replications of this study should preferably include a younger cohort of children or adolescents to test whether the effects would remain significant in a younger group. Although we used data over a relatively long period of time, a prospective study that would cover the pre-adolescence period, adolescence, and young adulthood, would be very interesting. Third, it is possible that our findings are affected by selective drop-out, as attrition analyses showed that adolescents with lower education and more smoking friends were more likely to drop-out of the study. Lower education level (Hanson & Chen,
2007) and more smoking friends (Hoffman et al.,
2006; Kobus,
2003) are associated with higher levels of smoking, so caution is warranted when interpreting and generalizing our findings. Nevertheless, selective drop-out in our study was limited. Finally, generalizability to the larger population was limited since we only included intact families from Dutch origin (i.e., mother, father, and two children). Previous studies have shown higher smoking prevalence rates in adolescents from single-parent rather than two-parent families (Brown & Rinelie,
2010; Lonczak et al.,
2007).
In sum, the current findings showed that smoking initiation risks were quite similar throughout mid- and late adolescence and that refusal self-efficacy is an important longitudinal predictor of smoking onset and self-efficacy is independent of smoking-specific communication and smoking behavior of parents, sibling, and (best) friend(s). The results imply the importance of prevention programs that focus on teaching skills for resisting social pressure to use tobacco by helping adolescents to develop personal self-management and social skills (e.g., Life Skills Training: Botvin et al.,
2003). Such interventions, with a recurrent character, could contribute to lower smoking onset rates in adolescents.