Predicting the development of diabetes using the product of triglycerides and glucose: the Chungju Metabolic Disease Cohort (CMC) study.
Seung-Hwan Lee, Hyuk-Sang Kwon, Yong-Moon Park, Hee-Sung Ha, Seung Hee Jeong, Hae Kyung Yang, Jin-Hee Lee, Hyeon-Woo Yim, Moo-Il Kang, Won-Chul Lee, Ho-Young Son, Kun-Ho Yoon
Author Information
Seung-Hwan Lee: Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, Seoul, Korea.
Hyuk-Sang Kwon: Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, Seoul, Korea.
Yong-Moon Park: Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, United States of America.
Hee-Sung Ha: Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Seung Hee Jeong: Clinical Research Coordinating Center, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Hae Kyung Yang: Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, Seoul, Korea.
Jin-Hee Lee: Catholic Institute of U-Healthcare, The Catholic University of Korea, Seoul, Korea.
Hyeon-Woo Yim: Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Clinical Research Coordinating Center, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Moo-Il Kang: Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, Seoul, Korea.
Won-Chul Lee: Department of Preventive Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.
Ho-Young Son: Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, Seoul, Korea.
Kun-Ho Yoon: Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, Seoul, Korea.
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: The TyG index, a simple measure reflecting insulin resistance, might be useful in identifying individuals at high risk of developing diabetes.
References
J Am Heart Assoc. 2012 Aug;1(4):e000869
[PMID: 23130155]
