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HOME > J Prev Med Public Health > Volume 42(5); 2009 > Article
English Abstract Lifestyle and Metabolic Syndrome among Male Workers in an Electronics Research and Development Company.
Jun Pyo Myong, Hyoung Ryoul Kim, Yong Kyu Kim, Jung Wan Koo, Chung Yill Park
Journal of Preventive Medicine and Public Health 2009;42(5):331-336
DOI: https://doi.org/10.3961/jpmph.2009.42.5.331
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1Team of Health promotion, Division of Health and Sanitation, Chungcheongbuk-do Provincial Government, Korea.
2Department of Preventive Medicine & Industrial Medical Center, The Catholic University School of Medicine, Korea. cyclor@catholic.ac.kr

OBJECTIVES
The objectives of this study were to determine the relationship between lifestyle-implementation and metabolic syndrome in an electronics research and development company, and to provide a foundation for health providers of health management programs for setting priorities. METHODS: From July 1 to July 16, 2008 we carried out a descriptive cross-sectional survey. Consecutive workers of one R & D company in Seoul, Korea (N=2,079) were enrolled in study. A checklist for lifestyle (from the National Health Insurance Corporation) consisted of questions regarding diet, drinking, smoking and exercise. After the survey, researchers obtained data from health profiles for metabolic syndrome(waist-circumference, triglycerides, HDL cholesterol, blood pressure and fasting blood sugar level). Lifestyle was recorded as good or not good. Statistical analysis of metabolic syndrome and the lifestyle of subjects was done using multiple logistic regression analysis. RESULTS: The prevalence of metabolic syndrome in our study gropu was 13.3% (N=277). After adjustment for age, the adjusted odds ratios (odds ratio, 95% confidence intervals) for metabolic syndrome increased in proportion to the number of bad habits: two (1.72, 1.23-2.44), three (2.47, 1.73-3.56), and four (3.63, 2.03-6.34). Relative to subjects eating both vegetables and meat', the OR for 'meat' eaters was 1.66 (1.18-2.31). Compared with 'non-smokers and ever-smoker', the OR for 'current-smoker' was 1.62 (1.25-2.10). Compared with 'Healthy drinker', the OR for 'unhealthy drinker' was 1.38 (1.05-1.83). CONCLUSIONS: Poor lifestyle was associated with an increased likelihood of metabolic syndrome. These findings suggest that lifestyle-based occupational health interventions for young employees should include a specific diet, smoking cessation, and healthy-drinking programs.

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