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Clustering of other metabolic risk factors in subjects with metabolic syndrome
Authors:Shiun Dong Hsieh  Takashi Muto  Yasuji Arase
Affiliation:a Medical Center of Health Science, Toranomon Hospital, Tokyo, Japan
b Department of Public Health, Dokkyo Medical University School of Medicine, Tochigi, Japan
c Okinaka Memorial Institute for Medical Research, Tokyo, Japan
Abstract:Various anthropometric indices have been proposed for metabolic syndrome. We investigated the clustering of metabolic risk factors other than components of metabolic syndrome and physical activity in subjects with and without metabolic syndrome as defined by different anthropometric indices. The subjects comprised 6141 men and 2137 women who underwent routine health examinations in Tokyo. We compared metabolic risk factors (high low-density lipoprotein cholesterol, hyperuricemia, high γ-glutamyltransferase, fatty liver) and sedentary history in subjects with and without metabolic syndrome as defined by the American Heart Association by substituting various proposed anthropometric indices of abdominal obesity (waist circumference ≥85, ≥90, or ≥102 cm for men and ≥90, ≥80, or ≥88 cm for women; waist-to-height ratio ≥0.5 for both men and women). Irrespective of the anthropometric index or sex, the age-adjusted odds ratios for risk factors and sedentary history were all significantly greater in subjects with metabolic syndrome (men and women: 1.26∼1.35 and 2.06∼2.63 for high low-density lipoprotein cholesterol, 2.36∼2.60 and 3.88∼7.20 for hyperuricemia, 2.54∼3.02 and 2.92∼4.05 for high γ-glutamyltransferase, 4.42∼4.87 and 9.43∼12.27 for fatty liver, and 1.37∼1.50 and 1.43∼1.72 for sedentary history). Findings still persisted in those not receiving medication for diabetes mellitus or coronary heart disease. Therefore, attention should be paid to other metabolic risk factors in subjects with metabolic syndrome, irrespective of the anthropometric index or sex. Further study is also needed to clarify the most appropriate definition of metabolic syndrome so as to include the spectrum of risk factors that best represents the future risk of cardiovascular and other diseases.
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