Comparison of the triglyceride glucose index and modified triglyceride glucose indices in assessing periodontitis in Korean adults.
glucose
insulin resistance
periodontitis
triglycerides
Journal
Journal of periodontal research
ISSN: 1600-0765
Titre abrégé: J Periodontal Res
Pays: United States
ID NLM: 0055107
Informations de publication
Date de publication:
Jun 2023
Jun 2023
Historique:
revised:
02
02
2023
received:
19
09
2022
accepted:
07
02
2023
medline:
15
5
2023
pubmed:
26
2
2023
entrez:
25
2
2023
Statut:
ppublish
Résumé
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. 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). 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). 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.
Sections du résumé
BACKGROUND
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
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
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
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.
Substances chimiques
Glucose
IY9XDZ35W2
Triglycerides
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
503-510Subventions
Organisme : Korea Evaluation Institute of Industrial Technology (KEIT) grant funded by the Korea Government (MOTIE)
ID : 20018384
Organisme : Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry
ID : 321030051HD030
Informations de copyright
© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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