Comparison of the triglyceride glucose index and modified triglyceride glucose indices in assessing periodontitis in Korean adults

Background Periodontal diseases are closely connected with insulin resistance (IR) and metabolic syndrome. The Triglyceride Glucose Index (TyG) assesses IR, and recently, a few indices combining TyG and body composition have emerged with higher IR predictive performance than TyG alone. We aimed to e...

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Published inJournal of periodontal research Vol. 58; no. 3; pp. 503 - 510
Main Authors Lee, Hyun‐Jeong, Lee, Ji‐Won, Kim, Sue, Kwon, Yu‐Jin
Format Journal Article
LanguageEnglish
Published United States Wiley Subscription Services, Inc 01.06.2023
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Summary:Background Periodontal diseases are closely connected with insulin resistance (IR) and metabolic syndrome. The Triglyceride Glucose Index (TyG) assesses IR, and recently, a few indices combining TyG and body composition have emerged with higher IR predictive performance than TyG alone. We aimed to examine which TyG‐related parameters are most helpful in predicting the risk of periodontal disease. Methods From 2013 to 2015, data were collected through the Korean National Health and Nutrition Examination Survey. Periodontitis was defined using the Community Periodontal Index. TyG‐body mass index (BMI), TyG‐waist circumference (WC), and TyG‐waist‐to‐height ratio (WHtR) were calculated by multiplying TyG index score by BMI, WC, and WHtR, respectively. Multiple logistic regression analysis was used to calculate odds ratio (OR) and 95% confidence intervals (CI). Receiver operating characteristic curves were used to estimate areas under the curve (AUC). Results Compared to each reference quartile (Q)1, Q4 of the TyG index, TyG‐BMI, TyG‐WC, and TyG‐WHtR were significantly associated with a higher risk of periodontitis after adjusting for confounders (OR, 95% CI; 1.23, 1.01–1.49 for TyG; 1.63, 1.22–2.17 for TyG‐BMI; 1.37, 1.04–1.81 for TyG‐WC; and 1.53, 1.16–2.02 for TyG‐WHtR). The AUC and 95% CIs of TyG, TyG‐BMI, TyG‐WC, and TyG‐WHtR in predicting periodontitis were 0.609 (0.600–0.617), 0.605 (0.596–0.617), 0.629 (0.621–0.637), and 0.636 (0.628–0.644), respectively (all p < .001). Conclusions TyG, TyG‐BMI, TyG‐WC, and TyG‐WHtR appear to be significantly associated with the prevalence of periodontitis. Among the TyG and modified TyG indices, TyG‐WHtR exhibited the highest predictive performance for periodontitis.
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ISSN:0022-3484
1600-0765
DOI:10.1111/jre.13108