Frontiers in public health · 2023
Prediction and potential risk factors for electronic cigarette use behaviors among adolescents: a pilot study in Chiayi, Taiwan.
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Liu Ping-I, Lin Ming-Nan, Ho Pei-Shan, Tsai Jui-Hsiu, Yang Ya-Hui, Wu Ke-Fei, Chuang Hung-Yi
Аннотация
INTRODUCTION: Electronic cigarette (e-cigarette) use among adolescents has become increasingly common; therefore, effectively reducing adolescent e-cigarette use is an urgent issue. We aimed to predict and identify potential factors related to adolescent e-cigarette use behaviors.
METHODS: This cross-sectional study was conducted using anonymous questionnaires given to Taiwanese high school students in 2020. Approximately 1,289 adolescent students completed questions on e-cigarette use, personal characteristics, family environment, and substances used. We performed multivariate logistic regression analyses to assess the model's predictive performance in terms of the area under the receiver operating characteristic curve.
RESULTS: We found that 9.3% of adolescent students used e-cigarettes. Tobacco smoking, close friends' reactions to e-cigarette use, and the use of other substances were independent risk factors for adolescent e-cigarette use. Furthermore, relative to tobacco nonuse, tobacco use and tobacco smoking dependence had odds ratios of 76.49 and 113.81, respectively. The predictive accuracy of adolescent e-cigarette use from personal characteristics, family environment, and substance use status was 73.13, 75.91, and 93.80%, respectively.
CONCLUSION: The present study highlights the need for early prevention of e-cigarette use among adolescents, particularly those with a history of using tobacco and other substances and those who have close friends with positive attitudes towards e-cigarette use.
METHODS: This cross-sectional study was conducted using anonymous questionnaires given to Taiwanese high school students in 2020. Approximately 1,289 adolescent students completed questions on e-cigarette use, personal characteristics, family environment, and substances used. We performed multivariate logistic regression analyses to assess the model's predictive performance in terms of the area under the receiver operating characteristic curve.
RESULTS: We found that 9.3% of adolescent students used e-cigarettes. Tobacco smoking, close friends' reactions to e-cigarette use, and the use of other substances were independent risk factors for adolescent e-cigarette use. Furthermore, relative to tobacco nonuse, tobacco use and tobacco smoking dependence had odds ratios of 76.49 and 113.81, respectively. The predictive accuracy of adolescent e-cigarette use from personal characteristics, family environment, and substance use status was 73.13, 75.91, and 93.80%, respectively.
CONCLUSION: The present study highlights the need for early prevention of e-cigarette use among adolescents, particularly those with a history of using tobacco and other substances and those who have close friends with positive attitudes towards e-cigarette use.