Association between serum gamma-glutamyltransferase and prevalence of metabolic syndrome using data from the Korean genome and epidemiology study

Mi Young Lee, Dae Sung Hyon, Ji Hye Huh, Hae Kyung Kim, Sul Ki Han, Jang Young Kim, Sang Baek Koh

Research output: Contribution to journalArticle

Abstract

Background: The aim of this study was to determine whether there is a positive correlation between gamma-glutamyltransferase (GGT) levels and the prevalence of metabolic syndrome and whether GGT can be used as an easily checkable metabolic index using data from the large-scale Korean Genome and Epidemiology Study (KoGES). Methods: We obtained data of 211,725 participants of the KoGES. The collected data included age, sex, height, weight, waist circumference, and various biochemical characteristics, including serum GGT levels. The data of study participants who ingested more than 40 g/day of alcohol and who were diagnosed with metabolic syndrome at baseline was excluded. We analyzed the prevalence of metabolic syndrome according to GGT quartiles in both genders. Results: The GGT level was significantly higher in subjects with metabolic syndrome compared to normal subjects (37.92±48.20 mg/dL vs. 25.62±33.56 mg/dL). The prevalence of metabolic syndrome showed a stepwise increase with GGT quartiles in both male and female subjects. Compared to the lowest GGT quartile, the odds ratio was 1.534 (95% confidence interval [CI], 1.432 to 1.643), 1.939 (95% CI, 1.811 to 2.076), and 2.754 (95% CI, 2.572 to 2.948) in men and 1.155 (95% CI, 1.094 to 1.218), 1.528 (95% CI, 1.451 to 1.609), and 2.022 (95% CI, 1.921 to 2.218) in women with increasing GGT quartile. The cutoff value of GGT predicting risk of metabolic syndrome was 27 IU/L in men and 17 IU/L in women. Conclusion: We suggested that GGT could be an easily checkable marker for the prediction of metabolic syndrome.

Original languageEnglish
Pages (from-to)390-397
Number of pages8
JournalEndocrinology and Metabolism
Volume34
Issue number4
DOIs
Publication statusPublished - 2019 Dec 1

All Science Journal Classification (ASJC) codes

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology

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