A novel criterion for identifying metabolically obese but normal weight individuals using the product of triglycerides and glucose.
OBJECTIVE
Metabolically obese but normal weight (MONW) individuals constitute a subgroup of normal weight individuals that display impaired insulin sensitivity with a higher risk of developing diabetes, cardiovascular disease and mortality. We aimed to propose a novel criterion for defining MONW by examining the usefulness and the cutoff value of the TyG index, a product of the levels of triglycerides and glucose, in identifying MONW individuals. In addition, the performance of this criterion in predicting the future incidence of diabetes was assessed.


METHODS
A total of 7541 non-diabetic, normal weight (body mass index ⩾18.5 and <25 kg m(-)(2)) subjects were selected from the Korea National Health and Nutrition Examination Survey conducted in 2009-2010. Another 3185 participants with follow-up studies were selected from a prospective community-based cohort study. The TyG index was calculated as ln(fasting triglycerides (mg dl(-1)) × fasting glucose (mg dl(-1))/2).


RESULTS
The levels of the TyG index paralleled the prevalence of metabolic syndrome and its components. The cutoff value of the TyG index that reflected MONW based on the receiver operating characteristics analysis was 8.82 for men and 8.73 for women, with the area under the curve values being 0.855 and 0.868, respectively. The sensitivity and the specificity were 84.2 and 77.6% in men and 69.1 and 89.4% in women, respectively. Individuals designated as MONW, who have a normal weight and TyG levels higher than cutoff, displayed a metabolically unhealthy phenotype and an approximately twofold higher risk of developing diabetes compared with metabolically healthy normal weight subjects.


CONCLUSIONS
We propose a simple diagnostic criterion of MONW, which might be used to discriminate subjects with a higher risk of metabolic diseases.
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Seoul St Mary's Hospital, Seoul, Korea.
S-H
SH
Lee
Department of Medical Statistics, College of Medicine, The Catholic University of Korea, Seoul, Korea.
K
K
Han
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Seoul St Mary's Hospital, Seoul, Korea.
H K
HK
Yang
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Seoul St Mary's Hospital, Seoul, Korea.
H-S
HS
Kim
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Seoul St Mary's Hospital, Seoul, Korea.
J-H
JH
Cho
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Yeouido St Mary's Hospital, Seoul, Korea.
H-S
HS
Kwon
Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA.
Y-M
YM
Park
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Seoul St Mary's Hospital, Seoul, Korea.
B-Y
BY
Cha
1] Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea [2] Department of Internal Medicine, Division of Endocrinology and Metabolism, Seoul St Mary's Hospital, Seoul, Korea.
K-H
KH
Yoon