AIM: Explore the relationship between the triglyceride-glucose (TyG) index, along with its derivative indices, and the prevalence of cataracts. METHODS: Data from 20,497 participants in the 2005-2008 National Health and Nutrition Examination Survey (NHANES) were compiled. A final total of 4,499 individuals met the eligibility criteria. Cataract presence was assessed through a self-reported history of cataract surgery. The TyG index and its derivatives-TyG-waist-to-height ratio (WHtR), TyG-neutrophil-to-lymphocyte ratio (NLR), TyG-monocyte-to-lymphocyte ratio (MLR), TyG-log platelet-to-lymphocyte ratio (lgPLR), TyG-log systemic inflammation index (lgSII), and TyG-systemic inflammation response index (SIRI)-were calculated. Statistical analyses included multivariable logistic regression, restricted cubic spline (RCS) curves for nonlinear relationships, and receiver operating characteristic (ROC) analysis. RESULTS: Higher TyG indices were significantly associated with cataract presence (P <
0.001). Specifically, TyG-WHtR, TyG-NLR, TyG-lgPLR, TyG-lgSII, and TyG-SIRI exhibited positive correlations with cataract prevalence, even after adjustment for potential confounders (odds ratio [OR] = 1.17
95% confidence interval [CI]: 1.01, 1.37
P = 0.0403
[OR] = 1.01
95% [CI]: 1.00, 1.02
P = 0.0258
[OR] = 1.08
95% [CI]: 1.01, 1.16
P = 0.0223
[OR] = 1.08
95% [CI]: 1.03, 1.14
P = 0.001
[OR] = 1.02
95% [CI]: 1.00, 1.04
P = 0.0120). Furthermore, the stratified analysis showed that in the 61-85 age group, TyG-lgPLR and TyG-lgSII remained positively associated with cataract prevalence ([OR] = 1.09
95% [CI]: 1.01, 1.17
P = 0.024
[OR] = 1.08
95% [CI]: 1.02, 1.13
P = 0.005). RCS analysis revealed a linear association between these indices and cataracts, with no apparent threshold effect. ROC analysis indicated that TyG-MLR demonstrated the highest predictive ability for cataract presence. CONCLUSION: The study results indicate a positive association between TyG-related indicators and cataract the prevalence of cataracts in middle-aged and elderly individuals, suggesting that these markers may serve as practical biomarkers for identifying high-risk individuals. Early detection and management of metabolic and inflammatory factors could contribute to effective preventive strategies for cataract development in the elderly population.