The application of observational data in translational medicine: analyzing tobacco-use behaviors of adolescents

Abstract

Background: Translational Medicine focuses on "bench to bedside", converting experimental results into clinical use. The "bedside to bench" transition remains challenging, requiring clinicians to define true clinical need for laboratory study. In this study, we show how observational data (an eleven-year data survey program on adolescent smoking behaviours), can identify knowledge gaps and research questions leading directly to clinical implementation and improved health care. We studied gender-specific trends (2000-2010) in Italian students to evaluate the specific impact of various anti-smoking programs, including evaluation of perceptions of access to cigarettes and health risk.

Methods: The study used, ESPAD-Italia® (European School Survey Project on Alcohol and other Drugs), is a nationally representative sample of high-school students. The permutation test for joinpoint regression was used to calculate the annual percent change in smoking. Changes in smoking habits by age, perceived availability and risk over a 11-year period were tested using a gender-specific logistic model and a multinomial model.

Results: Gender-stratified analysis showed 1) decrease of lifetime prevalence, then stabilization (both genders); 2) decrease in last month and occasional use (both genders); 3) reduction of moderate use (females); 4) no significant change in moderate use (males) and in heavy use (both genders). Perceived availability positively associates with prevalence, while perceived risk negatively associates, but interact with different effects depending on smoking patterns. In addition, government implementation of public policies concerning access to tobacco products in this age group during this period presented a unique background to examine their specific impact on behaviours.

Conclusion: Large observational databases are a rich resource in support of translational research. From these observations, key clinically relevant issues can be identified and form the basis for further clinical studies. The ability to identify patterns of behaviour and gaps in available data translates into new experiments, but also impacts development of public policy and reveals patterns of clinical reality. The observed global decrease in use is countered by stabilization in number of heavy smokers. Increased cigarette cost has not reduced use. While perceived risk of smoking may prevent initial experimentation, how government policies impact the perception of risk is not easily quantifiable.

Figure 1

Timeline of anti-smoking intervention programs in Italy during period of ESPAD data collection.

Figure 2

Age-Adjusted Availability,Risk Perception and Smoking Prevalence in Italian students, from 2000 to 2009 (Joinpoint Trend). 1) perceived availability, 2) perceived risk, 3) prevalence of lifetime use, 4) last 30-days use, 5) occasional smokers, 6) moderate smokers, 7) heavy smokers. * Indicates a significant Annual Percent Change (APC).