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HOME > J Korean Acad Community Health Nurs > Volume 23(1); 2012 > Article
Original Article
The Effects of Lifestyle Factors on Metabolic Syndrome among Korean Adults
Mee Young Im, Young-Ran Lee, Suk Jung Han, Chung-Min Cho
Journal of Korean Academy of Community Health Nursing 2012;23(1):13-21.
DOI: https://doi.org/10.12799/jkachn.2012.23.1.13
Published online: March 31, 2012

1Associate Professor, Department of Nursing, Seoil College, Seoul, Korea.

2Associate Professor, Department of Nursing, Seoul Women's College of Nursing, Seoul, Korea.

3Associate Professor, Department of Nursing, Samyook University, Seoul, Korea.

4Professor, Department of Nursing, Sungshin Women's University, Seoul, Korea.

• Received: February 10, 2012   • Revised: March 21, 2012   • Accepted: March 21, 2012

Copyright © 2012 Korean Academy of Community Health Nursing

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  • Purpose
    The purpose of this study was to estimate the effects of lifestyle factors on metabolic syndrome (MS) among Korean adults (age≥20).
  • Methods
    A total of 7,798 subjects (weighted subjects=37,215,961) were recruited from the 2009 Fourth Korea National Health and Nutrition Examination Survey (KNHANES IV-3). Data were analyzed by t-test, χ2-test, and logistic regression in consideration of strata, cluster and weight as national data using the SAS 9.1 program.
  • Results
    The prevalence of MS by definition of AHA/NHLBI and waist circumference cutoff points for Koreans was 22.4%. The mean clinical MS score for MS patients was 3.4, but the mean score for the non-MS group was 1.2 out of 5.0. Among the lifestyle factors, smoking (OR=1.024), stress (0.546≤OR≤0.587) and drinking (OR=1.005) had significant influence on the MS risk and MS scores, but exercise did not.
  • Conclusion
    The results of this study indicate that further research is necessary on the effect of lifestyle factors on MS risk and nurses should focus on effective programs about smoking, stress and drinking for the prevention and reduction of MS risk.
Table 1
Comparison of Demographic Characteristics between MS and Non-MS Groups (N=7,798, wN=37,215,961)
jkachn-23-13-i001.jpg

Note. Missing cases are excepted.

MS=metabolic syndrome, Non-MS: Non-metabolic syndrome; wN=weighted sum of observations is based on 2005' estimated population by Statistics Korea; wSD=weighted standard deviation due to national wide data analysis.

Table 2
Comparison of Metabolic Syndrome Clinical Determinants between MS and Non-MS Groups (N=7,798, wN=37,215,961)
jkachn-23-13-i002.jpg

Note. Missing cases are excepted.

MS=metabolic syndrome, Non-MS: Non-metabolic syndrome; wN=weighted sum of observations is based on 2005' estimated population by Statistics Korea; wSD=weighted standard deviation due to national wide data analysis.

Table 3
Comparison of Lifestyle Factors between MS and Non-MS Groups (N=7,798, wN=37,215,961)
jkachn-23-13-i003.jpg

Note. Missing cases are excepted.

MS=metabolic syndrome, Non-MS: Non-metabolic syndrome; wN=weighted sum of observations is based on 2005' estimated population by Statistics Korea; wSD=weighted standard deviation due to national wide data analysis.

Table 4
Logistic regression model of Lifestyle Risk Factors (N=7,798, wN=37,215,961)
jkachn-23-13-i004.jpg

Note. Missing cases are excepted; Logistic regression model fit statistics (Wald χ2=207.75, DF=6, p<.001).

wN=weighted sum of observations is based on 2005' estimated population by Statistics Korea; SE=standard error; OR=odds ratio; CI=confidence interval.

The present research has been conducted by the Research Grant of Seoil University in 2010.

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