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Jee and Kim: A Structural Model for Health Risk Behavior of Late Adolescents: Based on 2010 Korea Adolescent Health Survey
Original Article

Journal of Korean Academy of Nursing 2014; 44(2): 179-188.

Published online: 30 April 2014

DOI: https://doi.org/10.4040/jkan.2014.44.2.179

A Structural Model for Health Risk Behavior of Late Adolescents: Based on 2010 Korea Adolescent Health Survey

Young-Ju Jee1, Young-Hae Kim2

1Department of Nursing, Kyungnam University, Changwon, Korea.

2College of Nursing, Pusan National University, Busan, Korea.

Address reprint requests to: Kim, Young-Hae. College of Nursing, Pusan National University, 49 Busandaehak-ro, Mulgeum-eup, Yangsan 626-870, Korea. Tel: +82-51-510-8305~7, Fax: +82-51-510-8308, ungaekim@pusan.ac.kr

Received 23 September 2013       Revised 21 October 2013       Accepted 3 March 2014

© 2014 Korean Society of Nursing Science

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0/) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

Abstract

Purpose

This study was done to construct and test a structural model to explain health risk behavior of late adolescents.

Methods

Data for this study were secondary data from the 2010 Korea Adolescent Health Survey based and 3,675 high school students who participated. Data were analyzed using SPSS 18.0 and AMOS 19.0 programs.

Results

After 7 lines were removed, fitness statistics for the hypothetical model were appropriate (χ2=559.13, p<.001, GFI=.98, SRMR=.03, RMSEA=.04, NFI=.88, IFI=.90, CFI=.90, TLI=.86, AIC=671.13). The result showed that drinking-smoking is directly affected by 5 variables (32.5%), obesity is directly affected by 2 variables (0.7%), lack of physical activity is directly affected by 5 variables (22.2%), skipping of breakfast is directly affected by 3 variables (11.9%), improper sleep is directly affected by 3 variables (7.5%), and psychological adaptation is directly affected by 4 variables (26.8%).

Conclusion

The results of this study, indicate that late adolescents' health risk behavior is affected by many factors with complicate correlations suggesting further study compare youth health risk behaviors in a variety of environments.

Keywords: Health behavior, Adolescent, Smoking, Alcohols, Sleep

Figures and Tables

Figure 1
Hypothesis model with parameter estimates.
jkan-44-179-g001
Figure 2
Modified model.
jkan-44-179-g002
Table 1
Correlation of Variables (N=3,675)
jkan-44-179-i001

*p<.05; †p<.001; 1=Smoking; 2=Drinking; 3=Obesity; 4=Lack of physical activity; 5=Skipping of breakfast; 6=Improper sleep; 7=Self-esteem; 8=Self-efficacy, 9=Depression; 10=Anxiety; 11=Gender; 12=Address; 13=School level; 14=Parents' education level; 15=Interested in health by parents of students; 16=Family relationships; 17=Student's health concerns.

Table 2
Validation of Fit Hypothesis Model and the Modified Model
jkan-44-179-i002

df=degree of freedom; GFI=Goodness of Fit Index; SRMR=Standardized Root Mean Square Residual; RMSEA=Root Mean Square Error of Approximation; NFI=Normed Fit Index; IFI=Incremental Fit Index; CFI=Comparative Fit Index; TLI=Tucker Lewis Index; AIC=Akaike Information Criterion.

Notes

This manuscript is based on a part of the first author's doctoral dissertation from Pusan National University.

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