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Ágnes Kovács-Dániel Somoskői<br />

Eötvös Loránd University, <strong>Faculty</strong> <strong>of</strong> Pedagogy <strong>and</strong> Psychology, Budapest, Hungary<br />

Supervisor: Dr. Róbert Urbán, associate pr<strong>of</strong>essor<br />

Smoking <strong>and</strong> <strong>Physical</strong> Activity<br />

Introduction: The Budapest adolescent smoking study is a longitudinal study on the<br />

determinants <strong>of</strong> smoking. Our main goal was to test the cross-sectional association between<br />

level <strong>of</strong> physical activity/inactivity <strong>and</strong> smoking.<br />

Participants <strong>and</strong> procedure: The sample was composed <strong>of</strong> 2565 high school students (mean<br />

age = 15.3 years, sd = 0.56 years; 1251 boys <strong>and</strong> 1314 girls). The participants were asked to<br />

complete the questionnaire in their classrooms within one class session.<br />

Measures: Measures included self-reported smoking, questions related to physical activity<br />

<strong>and</strong> inactivity (time spent watching television or playing computer games). Four levels <strong>of</strong><br />

smoking status were identified: never tried (37.7%), experimenter (tried it but did not smoke<br />

during the past 30 days, 31.1%), intermittent smokers (did not smoke every day during the<br />

past 30 days, 19.7%), <strong>and</strong> regular or established smokers (smoked every day during the past<br />

30 days, 11.5%).<br />

Method: All statistical analyses were performed with spss 17.0. A principal component<br />

analysis <strong>of</strong> physical activity <strong>and</strong> inactivity questions analysis revealed two principal<br />

components, namely physical activity <strong>and</strong> physical inactivity. The two components explain<br />

54.5% <strong>of</strong> variance. The st<strong>and</strong>ardized score <strong>of</strong> the components are used in latter analyses.<br />

Analysis <strong>of</strong> variance (anova) <strong>of</strong> physical activity <strong>and</strong> inactivity. Two-way anova analyses<br />

were performed on physical activity <strong>and</strong> physical inactivity scores.<br />

Results: Significant main effects were found in physical activity component along gender <strong>and</strong><br />

smoking status (f(3)=6.2, p

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