Int Dent J. 2026 Jul 16;76(5):109755. doi: 10.1016/j.identj.2026.109755. Online ahead of print.
ABSTRACT
INTRODUCTION AND AIM: Insulin resistance and obesity are significant metabolic risk factors for periodontitis. This study aimed to systematically investigate the association between the novel metabolic obesity composite index, triglyceride glucose-a body shape index (TyG-ABSI), and the risk of periodontitis, further evaluating its clinical predictive performance.
METHODS: Data from 4545 participants were obtained from the National Health and Nutrition Examination Survey (NHANES) 2009 to 2014. To investigate the relationship between TyG-ABSI and the risk of periodontitis, weighted multivariable logistic regression models and restricted cubic spline (RCS) analyses were used. Exploratory mediation analysis was conducted to assess the statistical contributions of potential related factors to the association between TyG-ABSI and periodontitis. Predictive models were constructed using various machine learning (ML) algorithms. Model performance was evaluated and compared using the receiver operating characteristic curve, calibration curve, decision curve analysis, net reclassification improvement and integrated discrimination improvement.
RESULTS: A significant positive association was observed between TyG-ABSI and periodontitis risk (OR = 1.193, 95% CI: 1.089-1.308), with the highest tertile conferring a 2.25-fold elevated risk relative to the lowest tertile (OR = 2.252, 95% CI: 1.428-3.550). Restricted cubic spline analysis suggested a linear dose-response relationship. Subgroup analysis revealed a significant interaction with age, with the highest risk observed in individuals aged 45 to 59 years (OR = 1.320, 95% CI: 1.110-1.560). Exploratory mediation analysis showed that HbA1c and WBC accounted for 38.8% and 12.2% of the total association between TyG-ABSI and periodontitis, respectively. Machine learning models further suggested that the TyG-ABSI index has potential value in periodontitis risk prediction.
CONCLUSION: The novel composite index TyG-ABSI exhibits a significant positive association with periodontitis risk. It can serve as a reference indicator for periodontitis risk prediction.
CLINICAL RELEVANCE: TyG-ABSI integrates information related to insulin resistance and abdominal obesity. The present findings suggest that individuals with this metabolic-body shape abnormality phenotype should pay greater attention to their periodontal health status.
PMID:42462349 | DOI:10.1016/j.identj.2026.109755
