OBJECTIVE: This study assessed whether smoking in the movies was associated with smoking in young adults. METHODS: A national web-enabled cross-sectional survey of 1528 young adults, aged 18-25, was performed between September and November 2005. Logistic regression and path analysis using probit regression were used to assess relationships between exposure to smoking in the movies and smoking behavior. Analysis was completed in December 2006. RESULTS: Exposure to smoking in the movies predicted current smoking. The adjusted odds of current smoking increased by a factor of 1.21 for each quartile increase in exposure to smoking (p<0.01) in the movies, reaching 1.77 for the top exposure quartile. The unadjusted odds of established smoking (100+ cigarettes with current smoking) increased by 1.23 per quartile (p<0.001) of exposure, reaching 1.86 for the top quartile. This effect on established smoking was mediated by two factors related to smoking in the movies: positive expectations about smoking and exposure to friends and relatives who smoked, with positive expectations accounting for about two thirds of the effect. CONCLUSIONS: The association between smoking in the movies and young adult smoking behavior exhibited a dose-response relationship; the more a young adult was exposed to smoking in the movies, the more likely he or she would have smoked in the past 30 days or have become an established smoker.
OBJECTIVE: This study assessed whether smoking in the movies was associated with smoking in young adults. METHODS: A national web-enabled cross-sectional survey of 1528 young adults, aged 18-25, was performed between September and November 2005. Logistic regression and path analysis using probit regression were used to assess relationships between exposure to smoking in the movies and smoking behavior. Analysis was completed in December 2006. RESULTS: Exposure to smoking in the movies predicted current smoking. The adjusted odds of current smoking increased by a factor of 1.21 for each quartile increase in exposure to smoking (p<0.01) in the movies, reaching 1.77 for the top exposure quartile. The unadjusted odds of established smoking (100+ cigarettes with current smoking) increased by 1.23 per quartile (p<0.001) of exposure, reaching 1.86 for the top quartile. This effect on established smoking was mediated by two factors related to smoking in the movies: positive expectations about smoking and exposure to friends and relatives who smoked, with positive expectations accounting for about two thirds of the effect. CONCLUSIONS: The association between smoking in the movies and young adult smoking behavior exhibited a dose-response relationship; the more a young adult was exposed to smoking in the movies, the more likely he or she would have smoked in the past 30 days or have become an established smoker.
Authors: James D Sargent; Madeline A Dalton; Michael L Beach; Leila A Mott; Jennifer J Tickle; M Bridget Ahrens; Todd F Heatherton Journal: Am J Prev Med Date: 2002-04 Impact factor: 5.043
Authors: James D Sargent; Michael L Beach; Madeline A Dalton; Linda Titus Ernstoff; Jennifer J Gibson; Jennifer J Tickle; Todd F Heatherton Journal: Pediatrics Date: 2004-07 Impact factor: 7.124
Authors: Anna V Wilkinson; Margaret R Spitz; Alexander V Prokhorov; Melissa L Bondy; Sanjay Shete; James D Sargent Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-12 Impact factor: 4.254
Authors: James F Thrasher; James D Sargent; Liling Huang; Edna Arillo-Santillán; Ana Dorantes-Alonso; Rosaura Pérez-Hernández Journal: Cancer Epidemiol Biomarkers Prev Date: 2009-12 Impact factor: 4.254