Email updates

Keep up to date with the latest news and content from BMC Pediatrics and BioMed Central.

Open Access Research article

A prognostic tool to identify adolescents at high risk of becoming daily smokers

Igor Karp12*, Gilles Paradis345, Marie Lambert67, Erika Dugas1 and Jennifer O'Loughlin125

Author Affiliations

1 University of Montréal Hospital Research Centre (CRCHUM), Montreal, Quebec, Canada

2 Department of Social and Preventive Medicine, University of Montréal, Montreal, Quebec, Canada

3 Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

4 McGill University Health Center Research Institute, Montreal, Quebec, Canada

5 Institut national de santé publique du Québec, Montreal, Quebec, Canada

6 Centre de recherche de CHU Ste-Justine, Montreal, Quebec, Canada

7 Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada

For all author emails, please log on.

BMC Pediatrics 2011, 11:70  doi:10.1186/1471-2431-11-70

Published: 11 August 2011

Abstract

Background

The American Academy of Pediatrics advocates that pediatricians should be involved in tobacco counseling and has developed guidelines for counseling. We present a prognostic tool for use by health care practitioners in both clinical and non-clinical settings, to identify adolescents at risk of becoming daily smokers.

Methods

Data were drawn from the Nicotine Dependence in Teens (NDIT) Study, a prospective investigation of 1293 adolescents, initially aged 12-13 years, recruited in 10 secondary schools in Montreal, Canada in 1999. Questionnaires were administered every three months for five years. The prognostic tool was developed using estimated coefficients from multivariable logistic models. Model overfitting was corrected using bootstrap cross-validation. Goodness-of-fit and predictive ability of the models were assessed by R2, the c-statistic, and the Hosmer-Lemeshow test.

Results

The 1-year and 2-year probability of initiating daily smoking was a joint function of seven individual characteristics: age; ever smoked; ever felt like you needed a cigarette; parent(s) smoke; sibling(s) smoke; friend(s) smoke; and ever drank alcohol. The models were characterized by reasonably good fit and predictive ability. They were transformed into user-friendly tables such that the risk of daily smoking can be easily computed by summing points for responses to each item. The prognostic tool is also available on-line at http://episerve.chumontreal.qc.ca/calculation_risk/daily-risk/daily_smokingadd.php webcite.

Conclusions

The prognostic tool to identify youth at high risk of daily smoking may eventually be an important component of a comprehensive tobacco control system.