• Journal of Preventive Medicine and Public Health
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• v.52 no.4
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• pp.234-241
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• 2019

Objectives: To identify simultaneous behavioral changes in alcohol consumption, smoking, and weight using a fixed-effect model and to characterize their associations with disease status. Methods: This study included 7 000 529 individuals who participated in the national biennial health-screening program every 2 years from 2009 to 2016 and were aged 40 or more. We reconstructed the data into an individual-level panel dataset with 4 waves. We used a fixed-effect model for smoking, heavy alcohol drinking, and overweight. The independent variables were sex, age, lifestyle factors, insurance contribution, employment status, and disease status. Results: Becoming a high-risk drinker and losing weight were associated with initiation or resumption of smoking. Initiation or resumption of smoking and weight gain were associated with non-high-risk drinkers becoming high-risk drinkers. Smoking cessation and becoming a high-risk drinker were associated with normal-weight participants becoming overweight. Participants with newly acquired diabetes mellitus, ischemic heart disease, stroke, and cancer tended to stop smoking, discontinue high-risk drinking, and return to a normal weight. Conclusions: These results obtained using a large-scale population-based database documented interactions among lifestyle factors over time.

• Journal of the Korean Society of School Health
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• v.31 no.1
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• pp.10-17
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• 2018

Purpose: The purpose of this study was to examine the health behaviors and health status of adolescents in multicultural families according to gender. Methods: The study used raw data of the Korean Youth Risk Behavior Web-Based Survey performed in 2016. The 12th survey was conducted on 67,983 adolescents in 400 middle schools and 400 high schools. Among them, 759 adolescents were included in this study. Their data were analyzed using descriptive statistics, $x^2$-test, and Pearson's correlation. Results: There were significant differences in economic status, smoking experience, age of drinking onset, vigorous physical activity, soft drink consumption, toothbrushing after lunch, handwashing with soap before eating at school and eating at home and after coming home, BMI, subjective health status, stress, depression, and allergic rhinitis according to gender in multicultural adolescents. For boys, significant positive correlations were found between age and the age of drinking onset, between academic achievement and economic status, and between the age of smoking initiation and the age of drinking onset. However, there were significant negative correlations between economic status and stress and between subjective health status and stress. For girls, age had positive correlations with academic achievement, the age of drinking onset, BMI, and stress and economic status had positive correlations with academic achievement, the age of smoking initiation, and subjective health status. Also, the age of smoking initiation had positive correlations with the age of drinking onset and BMI. Lastly, there were negative correlations between age and economic status, between age and subjective health status, academic achievement and the age of smoking initiation, economic status and stress, and subjective health status and stress. Conclusion: The results of this study are expected to be useful as basic data for planning health interventions for boys and girls in multicultural families.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.45-50
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• 2016

Background: The tobacco epidemic is a heralding health menace, particularly among college students. Tobacco usage among young can have an especially devastating effect as they can be exposed for longer periods. Data to estimate the prevalence of tobacco use in young adults will be a valuable addition to the existing resources. Materials and Methods: An analytical cross-sectional study was therefore carried out in Mangalore city using a pre-tested, self-administered questionnaire adapted from the Global Youth Tobacco Survey (GYTS) with a representative sample of 720 students aged 18-20 years selected from degree colleges by multi-stage random sampling. Results: Prevalence of 'ever users' and 'current users' of smoking were 20.4% and 11.4%, respectively. The mean age at initiation of cigarette smoking was 16 years and the majority (31 %) smoked in public places. Interestingly, 84% of them knew about the harmful effects of cigarette smoking. About one half of smokers had some or most of their friends smoking. Multivariate analysis revealed gender (OR=8.585: CI-3.26-22.5), pocket money (OR=4.165; CI=1.76-9.82) and peer's smoking habit (OR= 5.15; CI-2.21-11.9) have higher odds as correlates of tobacco usage among college students. Conclusions: It is of prime importance to highlight the role of prevention of smoking initiation rather than subsequently trying to stop the habit. Comprehensive interventions embracing family, friends and social milieu are needed to reduce tobacco use among students in India.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.8 no.1
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• pp.51-68
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• 2001

The purpose of this study was to explain the relationship between smoking status, smoking behavior and hardiness in university students in Gangnung City. The subjects were a convenience sample of 315 students. The data were collected by a questionnaire given to the students between May 22 to June 2, 2000. An instrument developed by Akers & Gang(1996) and translated by Sohn, Jung-Nam(1999) was used in this study to measure definition of smoking, differential reinforcement of smoking and smoking behavior. The differential peer association scale developed Krohn et al.(1982) and translated by Sohn, Jung-Nam(1999), and the hardiness scale developed by Pollock(1984) and translated by Suh, Mun-Sa(1988) were also used. The data were analyzed using the SAS/PC+ Program and included descriptive statistics, t-test, ANOVA, and Spearman correlation coefficients. The results of this study are as follows : 1. The smoking rate for university students was 50.5% of which 44.7% started smoking in high school. 2. The mean score for level of hardiness was $3.14{\pm}0.43$ 3. The mean score for smoking behavior was as follows : 1) The mean score for the neutralizing definition was $2.16{\pm}0.57$ 2) The mean score for the negative definition was $2.37{\pm}0.71$ 3) The mean score for the positive differential reinforcement was $1.89{\pm}0.63$ 4) The mean score for the negative differential reinforcement was $2.96{\pm}0.64$ 5) The mean score for the differential peer association was $2.67{\pm}1.05$ 4. The data showed positive correlations between hardiness and the neutralizing definition(r=.1951, P<.001), between hardiness and the positive differential reinforcement(r=.1128, P<.05), between hardiness and the amount of smoking per day(r=.1452, P<.05) between the neutralizing definition and positive differential reinforcement(r=.4212, P<.0001), between the neutralizing definition and differential peer association(r=.1856, P<.001), between the neutralizing definition and age at smoking initiation(r=.1582, P<.05), between the negative definition and negative differential reinforcement(r=.2985, P<.0001), between the positive differential reinforcement and differential peer association(r=.3451, P<.0001), between positive differential reinforcement and the amount of smoking per day(r=.4431, P<.0001), between differential peer association and the duration of smoking(r=.2789, P<.0001), between differential peer association and the amount of smoking per day(r=.5410, P<.0001), between the duration of smoking and the amount of smoking per day(r=.4245, P<.0001). The data showed negative correlations between the neutralizing definition and the negative definition(r=-.2065, P<.001) between the neutralizing definition and negative differential reinforcement(r=-.3943, P<.0001) between the neutralizing definition and duration of smoking(r=-.1957, P<.05), between the negative definition and positive differential reinforcement(r=-.2093, P<.001), between the negative definition and the amount of smoking per day(r=-.2282, P<.001), between positive differential reinforcement and negative differential reinforcement(r=-.5555, P<.0001) between negative differential reinforcement and differential peer association(r=-.3653, P<.0001), between negative differential reinforcement and the amount of smoking per day(r=-.4570, P<.0001), between the age at smoking initiation and the duration of smoking(r=-.4594, P<.0001).

• 대한예방의학회:학술대회논문집
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• 2004.10a
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• pp.42.2-42.2
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• 2004

• Child Health Nursing Research
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• v.15 no.4
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• pp.367-374
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• 2009

Purpose: The purpose of this study was to identify the relationship of knowledge and attitude to temptation toward cigarette smoking in adolescents. Methods: A survey was conducted using a 52-item questionnaire in 2 high school settings. Descriptive statistics, t-tests, ANOVA, post hoc analysis and Pearson correlation coefficients were used with SPSS WIN version 14.0 to analyze the data. Results: There were significant differences in attitude toward smoking and smoking temptation depending on gender, academic performance, religion, current smoking status, parental responses toward smoking, initiation of smoking, and the number of friends who smoke (p<.001). The level of smoking knowledge was not related to any of general characteristics as well as attitude toward smoking and smoking temptation. However, negative attitude toward smoking was moderately correlated with reduced smoking temptation (r=-.608, p<.001). Conclusion: Adolescents' attitude toward smoking and coping ability against smoking temptation were influenced by various factors related to smoking behavior and social situations, rather than by the level of smoking knowledge. In order to develop an effective smoking prevention and cessation program for adolescents, various strategies to change attitudes toward smoking should be included.

• Journal of Korean Academy of Nursing
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• v.36 no.4
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• pp.612-620
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• 2006

Purpose. Smoking is the leading cause of death and smoking initiation rarely occurs after adolescence. Thus research on adolescent smoking is crucial. A consistent definition of smoking is important because inconsistent definitions make comparisons across studies an arduous task. Thus, the aim of the study was to suggest future research directions for smoking definitions after examining pitfalls in the literature. Methods. In this study the literature on adolescent smoking in the U.S. and South Korea was examined, and three types of smoking definitions were identified. Limitations in the studies are identified and future research directions are suggested. Results. In the U.S. literature, smoking definitions can be categorized into three groups: definitions based on stage models, smoking trajectories, and definitions derived from specific data. In the South Korean literature, various levels of smoking have not been differentiated. Conclusions. While the literature does not provide a definitive answer regarding the definition of smoking, it suggests three issues to consider for future research. First, multiple measures of smoking are more desirable than a one-time measure. Second, theory- or trajectory-based smoking definitions are more desirable than definitions derived from available data. Finally, regularity and amount of cigarette use should be incorporated in defining smoking behavior.

• Korean Journal of Health Education and Promotion
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• v.23 no.2
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• pp.29-45
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• 2006

Objectives: This study aims to investigate the attitude toward smoking and knowledge on smoking, self-efficacy, and self-esteem among high school students, and examine the moderate effects of gender on the differences in those variables between smoking and non-smoking students. As the result of investigation, it would suggest useful information for those who want to provide interventions of smoking prevention and smoking cessation to adolescents. Methods: Participants were 1,117 high school students (511 males, 584 females), whose mean age was 16.38 (SD=.87). To identify whether participants were smoking or not, bogus-pipeline was used. The data was collected with questionnaire include Smoking Attitude Inventory, General Self-Efficacy Scale, and Rosenberg's Self-Esteem Scale. A Pearson chi-square test and 2-way MANOVAs were performed with SPSS 11.5 for Windows. Results: With bogus-pipeline, one hundred thirty five (26.0%) of male students and 125(21.4%) of female students reported as they were smoking, while 115(22.2%) of male students and 78(13.3%) of female students reported as they were smoking at unidentified survey which was performed one week before bogus-pipeline. Results revealed that students who smoked had more positive attitude toward smoking and more knowledge on smoking than those who didn't smoke. Difference in knowledge on smoking between smoking and non-smoking students only existed in female students. Female students who smoked had lower self-esteem than female students who didn't smoke, but this difference didn't exist in male students. Conclusion: With the results of this study, it is considered smoking rates of adolescents surveyed with unidentified self-report questionnaires as underestimated. Health practitioners might consider female smokers' attitude toward and knowledge on smoking and self-esteem, especially for high school students. Despite of limitation of this study, it might help those who want to prevent initiation of smoking and give up smoking in adolescence.

• Korean Journal of Health Education and Promotion
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• v.17 no.2
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• pp.75-85
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• 2000

The National Health Promotion Law passed in 1995 was a milestone for initiating a national health promotion program in Korea, and local governments and health related organizations are developing and providing health promotion programs for the public. The purpose of this study was to explore the effectiveness of a smoking prevention video for adolescents. There was no educational video on smoking prevention for school students in Korea. Based on funding from the National Health Promotion Fund, an educational video on smoking prevention has been developed and tested for the effectiveness. The primary subject of the video was middle school students. The result of the study has shown that there was a statistically significant difference between pre-and post test among middle school students and elementary school students. Students' knowledge on the harm of smoking has been increased after the video education. In addition, more than half of the students responded that the educational video was interesting and helpful. To reduce initiation of smoking among adolescents, both policies and school health education programs should be reinforced. Policies on tobacco should focus on demand of smokers and potential smokers. So government officials should keep monitor obedience of the law on prohibition of smoking for those under age 19. School teachers should focus on social influence of smoking for adolescents.

• Child Health Nursing Research
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• v.25 no.4
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• pp.487-495
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• 2019

Purpose: We aimed to identify associations between the frequency of electronic cigarette (e-cigarette) use and smoking-related characteristics among adolescent smokers. Methods: We used data from the 14th Korea Youth Risk Behavior Survey. The participants were 3,722 smokers who had smoked cigarettes on at least one day during the past 30 days. The frequency of e-cigarette use was defined as the number of days that participants used e-cigarettes during the past 30 days, and was divided into four categories: 0, 1~2, 3~9, and ${\geq}10$ days. We used the $x^2$ test and multinomial logistic regression to examine the associations between the frequency of e-cigarette use and smoking-related characteristics. Results: Those who attempted to quit smoking, had used a heated tobacco product (HTP) at least once, or initiated e-cigarette use before middle school were more likely to use e-cigarettes for 3~9 days in the past 30 days. More frequent e-cigarette use (${\geq}10$ days) was associated with a higher frequency and greater amount of cigarette use, lifetime HTP use, and earlier initiation of e-cigarette use. Conclusion: Smoking-related characteristics differed by the frequency of e-cigarette use. Therefore, intervention programs targeting adolescent smokers should consider differences in smoking-related characteristics based on the frequency of e-cigarette use.