Smoking in young adolescents: an approach with multilevel discrete choice models

Abstract

Study objective: To understand the context for tobacco smoking in young adolescents, estimating the effects of individual, family, social, and school related factors. Design: Cross sectional analysis performed by multilevel logistic regression with pupils at the first level and schools at the second level. The data came from a stratified sample of students surveyed on their own, their families' and their friends' smoking habits, their schools, and their awareness of cigarette prices and advertising. Setting: The study was performed in the Island of Gran Canaria, Spain. Participants: 1877 students from 30 secondary schools in spring of 2000 (model's effective sample sizes 1697 and 1738) . Main results: 14.2% of the young teenagers surveyed use tobacco, almost half of them (6.3% of the total surveyed) on a daily basis. According to the ordered logistic regression model, to have a smoker as the best friend increases significantly the probability of smoking (odds ratio: 6.96, 95% confidence intervals (CI) (4.93 to 9.84), and the same stands for one smoker living at home compared with a smoking free home (odds ratio: 2.03, 95% CI 1.22 to 3.36). Girls smoke more (odds ratio: 1.85, 95% CI 1.33 to 2.59). Experience with alcohol, and lack of interest in studies are also significant factors affecting smoking. Multilevel models of logistic regression showed that factors related to the school affect the smoking behaviour of young teenagers. More specifically, whether a school complies with antismoking rules or not is the main factor to predict smoking prevalence in schools. The remainder of the differences can be attributed to individual and family characteristics, tobacco consumption by parents or other close relatives, and peer group. Conclusions: A great deal of the individual differences in smoking are explained by factors at the school level, therefore the context is very relevant in this case. The most relevant predictors for smoking in young adolescents include some factors related to the schools they attend. One variable stood out in accounting for the school to school differences: how well they enforced the no smoking rule. Therefore we can prevent or delay tobacco smoking in adolescents not only by publicising health risks, but also by better enforcing no smoking rules in schools. P recisely what leads adolescents to take up smoking has been the subject of exhaustive study in the recent epidemiological literature.

Association between home smoking restrictions and changes in smoking behaviour among employed women

“…In general, these studies found home smoking restricts were associated with several positive outcomes, including a reduced likelihood of adolescent initiation, an increased odds of being a former smoker, or being in an earlier stage of smoking update, compared with adolescents who lived in households with no restrictions. [32][33][34] Although, the association between smoke free homes and cessation in our analysis was highly significant (p,0.0001), it is not clear to what degree these differences in cessation can be directly attributed to the adoption of restrictive home policies. It is unknown, for example, how much of the association seen is attributable to women who quit because they live in a smoke free home and how much is attributable to women who are in the process of quitting adopting rules prohibiting smoking anywhere in the home.…”

“…20 Although the preponderance of studies published to date have focused on the workplace, evidence is now beginning to accumulate on the correlation between home smoking restrictions and changes in smoker behaviour among both adults [25][26][27][28][29][30][31] and adolescents. [32][33][34] Analysing data from the earlier 1992-93 CPS, Farkas et al found a statistically significant correlation between home smoking restrictions and both quit attempts and successful quitting, defined as quit for six or more months, among more than 48 000 adult smokers; furthermore, household restrictions were more strongly correlated with both cessation outcomes compared with workplace restrictions. 25 Using a stages of change model Pizacani et al conducted a 21 month follow up of 565 smokers to assess the association between home smoking restrictions and changes in smoking behaviour.…”

Factores asociados con el consumo diario de cigarrillo en adolescentes estudiantes de básica secundaria de Bucaramanga, Colombia.

“…Se observa una asociación significativa entre el consumo diario de cigarrillo y un patrón de consumo abusivo de alcohol (32). Es posible que esta diferencia esté relacionada con factores sociales y culturales en este rango de edad.…”

“…Es posible que esta diferencia esté relacionada con factores sociales y culturales en este rango de edad. Por otra parte, que el mejor amigo sea fumador se ha relacionado significativamente con consumo diario de cigarrillo (32)(33)(34)39). Una asociación similar se ha documentado cuando el contexto familiar, hermano, padres u otro familiar cercano son fumadores (33,(38)(39)(40).…”

Smoking behaviours and contextual influences on adolescent nicotine dependence

“…In particular, although adolescents may well feel the same urge to use tobacco products, it is possible that many are unable to fulfill this desire as easily as many adults. 7 Therefore, instruments that include measures of free or easy access to tobacco, such as smoking frequency and the number of cigarettes smoked, could register lower scores in adolescents than in adults with similar dependence levels. The Hooked on Nicotine Checklist (HONC) developed by DiFranza and colleagues does not have this limitation because it is based solely on the desire to use tobacco.…”