Milken Institute School of Public Health Poster Presentations (Marvin Center & Video)
Poster Number
25c
Document Type
Poster
Status
Recent Alumni
Abstract Category
Epidemiology and Biostatistics
Keywords
e-cigarettes, cigarettes, smoking, adolescents, youth tobacco
Streaming Media
Publication Date
Spring 2018
Abstract
Background/Objectives: Rates of cigarette smoking among adolescents have been trending downward, however rates of adolescent e-cigarette use rates are now twice those of adolescent cigarette smoking nationally. The objective of this study was to examine the association of demographic, socioeconomic, psychosocial and health behavioral factors as surveyed by the Minnesota Student Survey with cigarette smoking and e-cigarette use among Minnesota adolescents.
Methods: This study analyzed the 2016 Minnesota Student Survey (MSS), an anonymous, school-based, cross-sectional survey of students in grades five, eight, nine and eleven. The 2016 MSS contains a total of 168,733 records, 118,198 of which were analyzed for this study. Frequency analysis, Chi-square, and logistic regression models were used to assess for association of demographic, psychosocial and behavioral factors with student cigarette smoking and e-cigarette use.
Results: A total of 17,917 students reported using cigarettes or e-cigarettes in the past 30 days. Of these, 67.5% reported smoking e-cigarettes and 32.5% reported smoked cigarettes, while 22.5% (4015 students) reporting smoking both cigarettes and e-cigarettes. Students identifying as bisexual were over four times as likely (AOR=4.40 [95% CI 4.01, 4.82]) versus heterosexual-identified students to smoke cigarettes but only twice as likely (AOR=2.24 [95% CI 2.06, 2.43]) to use e-cigarettes, while students identifying as gay or lesbian were 2.75 times as likely (AOR 2.75 [95% CI 2.27, 3.34]) to smoke cigarettes and only 1.5 times as likely (AOR=1.50 [95% CI 1.24, 1.76]) to use e-cigarettes. Students receiving free/reduced lunch were nearly twice as likely (AOR=1.92 [95% CI 1.80, 2.05]) to smoke cigarettes versus students not receiving free/reduced lunch, but only 1.33 times as likely (AOR=1.33 [95% CI 1.27, 1.39]) to use e-cigarettes. Students reporting skipping meals due to family economic hardship were over 3.5 times as likely (AOR 3.63 [95% CI 3.33, 3.95]) to smoke cigarettes but only 2.79 times as likely (AOR=2.79 [95% CI 2.59, 2.99]) to use e-cigarettes. Both increasing levels of alcohol usage and decreasing levels of reported academic performance are linearly associated with increasing likelihood of both cigarette smoking and e-cigarette use, but in both cases more steeply with cigarette smoking versus e-cigarette use.
Conclusion: Results of this study expand on existing research demonstrating differences in the psychosocial and behavioral risk profiles for adolescent cigarette smokers versus e-cigarette users. Further understanding of these predictors is critical to informing comprehensive public health strategies targeting prevention and reduction of youth tobacco and nicotine use.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Open Access
1
(VIDEO) Differences in Psychosocial and Behavioral Risk Profiles of Cigarette Smokers and E-cigarette Users Among Minnesota Adolescents: 2016
Background/Objectives: Rates of cigarette smoking among adolescents have been trending downward, however rates of adolescent e-cigarette use rates are now twice those of adolescent cigarette smoking nationally. The objective of this study was to examine the association of demographic, socioeconomic, psychosocial and health behavioral factors as surveyed by the Minnesota Student Survey with cigarette smoking and e-cigarette use among Minnesota adolescents.
Methods: This study analyzed the 2016 Minnesota Student Survey (MSS), an anonymous, school-based, cross-sectional survey of students in grades five, eight, nine and eleven. The 2016 MSS contains a total of 168,733 records, 118,198 of which were analyzed for this study. Frequency analysis, Chi-square, and logistic regression models were used to assess for association of demographic, psychosocial and behavioral factors with student cigarette smoking and e-cigarette use.
Results: A total of 17,917 students reported using cigarettes or e-cigarettes in the past 30 days. Of these, 67.5% reported smoking e-cigarettes and 32.5% reported smoked cigarettes, while 22.5% (4015 students) reporting smoking both cigarettes and e-cigarettes. Students identifying as bisexual were over four times as likely (AOR=4.40 [95% CI 4.01, 4.82]) versus heterosexual-identified students to smoke cigarettes but only twice as likely (AOR=2.24 [95% CI 2.06, 2.43]) to use e-cigarettes, while students identifying as gay or lesbian were 2.75 times as likely (AOR 2.75 [95% CI 2.27, 3.34]) to smoke cigarettes and only 1.5 times as likely (AOR=1.50 [95% CI 1.24, 1.76]) to use e-cigarettes. Students receiving free/reduced lunch were nearly twice as likely (AOR=1.92 [95% CI 1.80, 2.05]) to smoke cigarettes versus students not receiving free/reduced lunch, but only 1.33 times as likely (AOR=1.33 [95% CI 1.27, 1.39]) to use e-cigarettes. Students reporting skipping meals due to family economic hardship were over 3.5 times as likely (AOR 3.63 [95% CI 3.33, 3.95]) to smoke cigarettes but only 2.79 times as likely (AOR=2.79 [95% CI 2.59, 2.99]) to use e-cigarettes. Both increasing levels of alcohol usage and decreasing levels of reported academic performance are linearly associated with increasing likelihood of both cigarette smoking and e-cigarette use, but in both cases more steeply with cigarette smoking versus e-cigarette use.
Conclusion: Results of this study expand on existing research demonstrating differences in the psychosocial and behavioral risk profiles for adolescent cigarette smokers versus e-cigarette users. Further understanding of these predictors is critical to informing comprehensive public health strategies targeting prevention and reduction of youth tobacco and nicotine use.