Adolescent smoking and nicotine dependence
Chapter 5 described which smoking characteristics of adolescents predict later nicotine dependence. The results illustrate that it is very important to prevent the transition to daily smoking in adolescents who are experimenting with smoking, in order to reduce young adult nicotine dependence (ND). Most of the adolescents’ smoking variables (adolescent maximum smoking level, onset of daily smoking, duration of smoking, escalation time, and quitting time) were only related to nicotine dependence when taking all smokers together. None of these variables predicted nicotine dependence within the subgroup of non- daily smokers, indicating that the most important factor predicting nicotine dependence in adolescent non-daily smokers seemed to be whether they progress to daily smoking. Concerning these non-daily smokers, it is important for tobacco control interventions to focus on the prevention of the transition to daily smoking, for instance by combining an increase in cigarette taxes with media campaigns, which is a cost-effective way to reduce the smoking prevalence (e.g., Fishman et al., 2005). Another important finding of this study was that among daily smokers, quitting for one year was sufficient to reduce the risk of nicotine dependence to a level similar to never smokers. This finding may have important implications for interventions. Programmes aimed at helping adolescents to quit smoking are mostly shorter than one year, and many adolescents relapse after the programme. Longer interventions programmes, with affordable strategies such as offering tailored, personalised, and regular text messaging (Rodgers et al., 2005) should be designed.
For adolescents with asthma, it is even more important to prevent ND, since nicotine dependence is one of the strongest predictors of failed smoking cessation attempts (e.g., Hyland et al., 2004). Nicotine dependence thus leads to continued use of tobacco, which is especially associated with health risks among people with asthma (Thomson et al., 2004). Chapter 6 demonstrated that if adolescents with asthma start smoking, they have an accelerated development of smoking behaviour, and will more often progress to regular
smoking. This transition to regular smoking is obviously a very important predictor of later nicotine dependence, and the findings in Chapters 5 and 6 together demonstrate that the transition to daily smoking in adolescents with asthma should be prevented. More research is needed to determine why adolescents with asthma have this accelerated development of smoking. Until then, strategies to reduce transition to daily smoking among the general population of adolescents may offer ways to prevent adolescents with asthma to become nicotine dependent. In addition, given the increased health risks and the increased prevalence of regular smoking in adolescents with asthma, it is very important to have interventions aim at daily smoking adolescents with asthma to help them quit for at least one year to decrease the risks of later ND.
Limitations
Although specific limitations of the studies in this thesis were described in the previous chapters, we would like to discuss some general limitations of our studies below.
Self-reported asthma
One important limitation is that asthma was assessed by self-reports. Because of the large sample size of this longitudinal study (10,087 adolescents participated in the first wave), it was not possible to use more objective physical measures of asthma. However, the questionnaires of ISAAC were designed for population based surveys and were used worldwide in epidemiological studies on atopic diseases in children and adolescents (e.g. Asher et al., 1995; 2006), and the questionnaires showed high validity to measure the prevalence of atopic diseases such as asthma (Asher et al., 1995; Shaw et al., 1995). Comparison of the ISAAC asthma questionnaire with a physician’s assessment of asthma demonstrated its sensitivity and specificity (Jenkins et al., 1996). The same was true for the symptoms questionnaire of the American College of Allergy, Asthma, and Immunology (ACAAI); the cut-off score of three or more affirmative responses (like we used in Chapter 6) had an estimated sensitivity of 80% and a specificity of 70% for the asthma clinical consensus designation according to a validation study (Redline et al., 2004). So, although the results in this thesis are based on self-reported asthma and symptoms of asthma, they seem to be valid. However, future research should preferably combine large population surveys with more objective asthma measures that are easy to assess (e.g., peak flow meters).
Self-reported smoking
Adolescent smoking behaviour was also assessed by self-reports. Although it is very common to use self-reports in studies on smoking behaviour, the validity of these self-reports could be questioned. For instance, smokers may underestimate or deny their smoking behaviour due to conforming to the social norms of not smoking (Patrick et al., 1994). However, several studies using biochemical markers of smoking, such as cotinine, thiocyanate, and carbon monoxide, indicated that self-reports on smoking are reliable and valid (see Patrick
et al., 1994, for a review and meta-analysis). This has been replicated in community studies (Vartiainen, Seppala, Lillsunde, & Puska, 2002) as well as in adolescent populations (Dolcini, Adler, Lee, & Bauman, 2003).
However, using self-reports in populations in which smoking is less socially accepted might be less reliable. For instance, a study among adolescents and young adults with diabetes demonstrated that self-reports on smoking were not reliable because many patients denied they were using tobacco (Holl, Grabert, Heinze, & Debatin, 1998). In contrast, research that compared self-reports with biological markers of smoking in pregnancy (which is also less socially accepted) showed that self-reported smoking status during pregnancy was highly accurate (e.g., McDonald, Perkins, & Walker, 2005), although other studies suggested that underreporting in this group was high (e.g. Boyd, Windsor, Perkins, & Lowe, 1998). To our knowledge, no studies investigated the reliability and validity of self-reported smoking in adolescents with asthma. However, since smoking is probably less socially accepted in adolescents with asthma compared to healthy adolescents, we cannot rule out that some adolescents with asthma underreported their smoking behaviour. The results of this thesis indicated that adolescents with asthma initiated smoking less often, but among smokers, adolescents with asthma were more often regular smokers. If smoking among this group was underreported to a larger degree, there would be more reason to have concerns about the smoking behaviour of adolescents with asthma. With regard to the predictors of smoking that we found for adolescents with asthma, it is difficult to see how this potential underreporting might have influenced the results. Possibly there are associations between some of these predictors and the underreporting of smoking. For instance, adolescents who tend to underreport smoking are probably overreporting adherence to medication regimens, and may report more negative smoking cognitions, thereby increasing the strength of the relations we found in this thesis. Future research on smoking in adolescents with asthma could benefit from using cotinine measures (e.g. in a random subsample) to increase validity and reliability of smoking measures in this group.
Smoking categorization
In the second part of this thesis, we studied the smoking behaviour of adolescents with and without asthma. Different smoking categorizations were used throughout this thesis. In Chapter 5 we differentiated between never smokers, non-daily smokers, and daily smokers (cf. Patton, Coffey, Carlin, Sawyer, & Lynskey, 2005; Patton, Coffey, Carlin, Sawyer, & Wakefield, 2006), closely resembling our categorization into never smokers, experimental smokers, and regular smokers in Chapter 6, although regular smokers were defined as weekly instead of daily smokers. Because of the young age of the respondents (14.8 years at follow-up), the prevalence of daily smoking was quite low, so we chose to label weekly smokers also as regular smokers. In Chapter 7 we distinguished nine categories of smokers (Kremers, Mudde, & De Vries, 2001) and analysed them on a 9-point Likert scale, whereas in Chapters 8 and 9, we dichotomized smoking. We had several reasons to use different categorizations throughout this thesis. Except for the study in Chapter 5, which was based on another data set, all studies measured smoking by 9 categories (see Appendix Chapter
8 for categories). However, only in the cross-sectional study of Chapter 7 it was possible to analyse all categories separately. In the studies of Chapters 6, 8, and 9 we included solely the baseline non-smokers, to longitudinally predict smoking initiation. Since only 29.4% of adolescents started smoking and due to the skewed distribution of the smoking categories, it was necessary to merge categories in the studies of these chapters.
In other recent publications of longitudinal studies that used the same nine category measure, smoking was recoded into 6 categories (never smokers, triers, experimenters, regular smokers, non-smoking deciders, and quitters) (e.g., De Vries et al., 2003; Kremers, Mudde, De Vries, Brug, & De Vries, 2004). To make research on smoking initiation, continuation and cessation more comparable, we would like to argue that it is essential for future research to strive for similar smoking measures and categorizations. With regard to studying smoking of adolescents with asthma, larger samples are needed to study initiation, progression, and cessation with more detailed smoking measures.
Cross-sectional design
Chapters 3 and 4 described cross-sectional studies that tried to gain insight into relations between personality, symptom severity, and coping on the one hand and quality of life of adolescents with asthma on the other. Because of the cross-sectional character of these studies, it is not possible to test causal relationships (Stigler, 2005). Although we assumed that the factors investigated in these chapters had effects on QOL of adolescents with asthma, we cannot rule out that some of the suggested relationships were reversed. With regard to personality, it is often assumed that personality is stable over time (McCrae & Costa, 1997). However, research demonstrated that personality is subject to change during adolescence, and changes in personality are related to changes in anxiety (Akse, Hale, Engels, Raaijmakers, & Meeus, 2007). It might be possible that for instance QOL might have influenced personality of adolescents with asthma instead of the other way round. Experiencing reduced QOL may, for instance, result in adolescents being more introverted. For other variables in our cross-sectional models, the temporal relation may be reversed as well. For instance, it is possible that ways of coping with asthma influences symptom severity instead of severity influencing coping. It is therefore important for future studies to replicate the results with longitudinal designs. And even with longitudinal designs, one should be careful with causal inferences, since a temporal relation between two variable does not necessarily mean causation, since a third variable may play a role as well (such as was suggested in Chapter 9 with the relation between adherence and smoking initiation, which was believed to be caused by other variables, such as personality). Prospective, experimental research is needed to determine causation (Kazantzis, Ronan, & Deane, 2001). Unfortunately, experimental research is definitely not always feasible. However, if future research will use longitudinal designs that measure all constructs at all time points, and if researchers will include all theoretically possible confounders, it will be possible to rule out alternative interpretations, thereby strengthening the causal explanation of findings.
In Chapter 7, a cross-sectional study on the relation between smoking-specific cognitions and smoking behaviour of adolescents with and without asthma was described. Again we
should be cautious with interpreting relations. In this cross-sectional study we found that cognitions were more strongly related to smoking behaviour in adolescents with asthma compared to non-asthmatic adolescents. Because of the design, it was impossible to conclude from this study whether having pro-smoking cognitions resulted in higher smoking initiation, especially for adolescents with asthma, or whether smoking behaviour led to a stronger change in smoking-specific cognitions for adolescents with asthma. In this case, we replicated the results with a longitudinal study (Chapter 8), showing that smoking-specific cognitions were stronger predictors of smoking onset in adolescents with asthma. However, caution is still necessary. The finding that cognitions predicted smoking initiation more strongly in adolescents with asthma did not rule out larger cognitive dissonance reduction in these adolescents with asthma. Both processes could work simultaneously, with cognitions influencing behaviour and behaviour influencing cognitions. Future longitudinal studies on the smoking behaviour of adolescents with asthma should include measures of smoking- specific cognitions and behaviour at all waves to determine if both processes are at work.
Common method biases
A last limitation of this study is that the results are subject to common method biases (see Podsakoff, MacKenzie, Lee, & Podsakoff, 2003 for a review). One important bias is the common rater effect: because the same respondent provides the measures of both the predictor and the dependent variable, the covariance might be overestimated. There are several reasons for this bias, one of them being that respondents want to be consistent in their answers, and look for similarities in questions, thereby producing relationships that would not exist without this consistency motif (e.g., Johns, 1994). Other reasons for this potential bias include the influence of mood (either trait or state), and the influence of implicit theories that respondents have on relations between variables. In addition to common rater effects, the results of this study might also be due to context effects, since all measures are assessed in the same (school) context, at the same time (for each wave, all questionnaires were filled out in that school hour) and using the same medium (paper and pencil questionnaire).