Korean J Fam Pract.  2021 Apr;11(2):127-134. 10.21215/kjfp.2021.11.2.127.

Effects of Mental Health and Drinking Behavior on Youth Smoking: Using the 2019 Youth Health Behavior Survey

• Lee T
• Lee M
• Shin M
• Kim S

• KMID: 2515051
• DOI: http://doi.org/10.21215/kjfp.2021.11.2.127

Abstract

Background
Using the results of the 2019 Youth Health Behavior Survey, this study examines youth mental health and drinking behaviors and their impact on youth smoking to suggest appropriate control methods for the youth smoking problem.
Methods
Of 60,100 students who participated in the 2019 survey, 57,303 responded completely to the survey. A total of three smoking statuses were set in this study; from which 7,680 (the smoking group) answered “yes,” and 49,623 (the non-smoking group) answered “no.” For this study, 13 cause variables were included using five social-demographic factors, four mental health factors, and four drinking behavior factors. Chi-square and multivariate logistic regression analyses were performed to identify the effect of the cause variables on the outcome variables.
Results
According to the analysis, sex, school grade, academic performance in the last year, sexual experience, stress recognition, fatigue recovery in the last seven days, sadness and despair experiences in the last year, and suicidal thinking in the last year are significant factors for smoking. Moreover, lifetime drinking experience, drinking days over the last 30 days, average drinking amount in the last 30 days, and being drunk in the last 30 days are also significant.
Conclusion
Specialized smoking-related guidance is necessary by considering sex, age, school type, academic performance, and sexual experience. An overall mental health management system including students sleeping patterns should be implemented to closely examine drinking behavior, which is strongly related to smoking, and approach drinking problems from an integrated perspective that includes smoking problems.

Keyword

Youth Smoking; Mental Health; Drinking Behavior; Logistic Regression Analysis