Details

Autor(en) / Beteiligte

• Lee, Seung-Hwan
• Kwon, Hyuk-Sang
• Park, Yong-Moon
• Ha, Hee-Sung
• Jeong, Seung Hee
• Yang, Hae Kyung
• Lee, Jin-Hee
• Yim, Hyeon-Woo
• Kang, Moo-Il
• Lee, Won-Chul
• Son, Ho-Young
• Yoon, Kun-Ho
• Saez, Maria Eugenia

Titel

Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju Metabolic Disease Cohort (CMC) study

Ist Teil von

• PloS one, 2014-02, Vol.9 (2), p.e90430-e90430

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2014

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• To determine whether the TyG index, a product of the levels of triglycerides and fasting plasma glucose (FPG) might be a valuable marker for predicting future diabetes. A total of 5,354 nondiabetic subjects who had completed their follow-up visit for evaluating diabetes status were selected from a large cohort of middle-aged Koreans in the Chungju Metabolic Disease Cohort study. The risk of diabetes was assessed according to the baseline TyG index, calculated as ln[fasting triglycerides (mg/dL) × FPG (mg/dL)/2]. The median follow-up period was 4.6 years. During the follow-up period, 420 subjects (7.8%) developed diabetes. The baseline values of the TyG index were significantly higher in these subjects compared with nondiabetic subjects (8.9 ± 0.6 vs. 8.6 ± 0.6; P<0.0001) and the incidence of diabetes increased in proportion to TyG index quartiles. After adjusting for age, gender, body mass index, waist circumference, systolic blood pressure, high-density lipoprotein (HDL)-cholesterol level, a family history of diabetes, smoking, alcohol drinking, education level and serum insulin level, the risk of diabetes onset was more than fourfold higher in the highest vs. the lowest quartile of the TyG index (relative risk, 4.095; 95% CI, 2.701-6.207). The predictive power of the TyG index was better than the triglyceride/HDL-cholesterol ratio or the homeostasis model assessment of insulin resistance. The TyG index, a simple measure reflecting insulin resistance, might be useful in identifying individuals at high risk of developing diabetes.