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HOME > J Prev Med Public Health > Volume 39(3); 2006 > Article
English Abstract Clustering of Metabolic Risk Factors and Its Related Risk Factors in Young Schoolchildren.
Kyoung Ae Kong, Bo Hyun Park, Jung Won Min, Juhee Hong, Young Sun Hong, Bo Eun Lee, Namsoo Chang, Sun Hwa Lee, Eun Hee Ha, Hyesook Park
Journal of Preventive Medicine and Public Health 2006;39(3):235-242
DOI: https://doi.org/
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1Department of Preventive Medicine, Ewha Womans University, Korea. hpark@ewha.ac.kr
2Department of Internal Medicine, Ewha Womans University, Korea.
3Division of Chronic Disease Surveillance, Korea Center for Disease Control and Prevention, Korea.
4Department of Food and Nutritioal Science, Ewha Womans University, Korea.
5Neodin Medical Institute, Korea.

OBJECTIVES
We wanted to determine the distribution of the clustering of the metabolic risk factors and we wanted to evaluate the related factors in young schoolchildren. METHODS: A cross-sectional study of metabolic syndrome was conducted in an elementary school in Seoul, Korea. We evaluated fasting glucose, triglyceride, HDL cholesterol, blood pressures and the body mass index, and we used parent-reported questionnaires to assess the potential risk factors in 261 children (136 boys, 125 girls). We defined the metabolic risk factors as obesity or at risk for obesity (> or = 85th percentile for age and gender), a systolic or diastolic blood pressure at > or = 90th percentile for age and gender, fasting glucose at > or = 110 mg/dl, triglyceride at > or = 110 mg/dl and HDL cholesterol at @40 mg/dl. RESULTS: There were 15.7% of the subjects who showed clustering of two or more metabolic risk factors, 2.3% of the subjects who showed clustering for three or more risk factors, and 0.8% of the subjects who showed clustering for four or more risk factors. A multivariate analysis revealed that a father smoking more than 20 cigarettes per day, a mother with a body mass index of = 25 kg/m2, and the child eating precooked or frozen food more than once per day were associated with clustering of two or more components, with the odds ratios of 3.61 (95% CI=1.24-10.48), 5.50 (95% CI=1.39-21.73) and 8.04 (95% CI=1.67-38.81), respectively. CONCLUSIONS: This study shows that clustering of the metabolic risk factors is present in young schoolchildren in Korea, with the clustering being associated with parental smoking and obesity as well as the child's eating behavior. These results suggest that evaluation of metabolic risk factors and intervention for lifestyle factors may be needed in both young Korean children and their parents.

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JPMPH : Journal of Preventive Medicine and Public Health