Abstract Insulin resistance (IR) and obesity represent two major factors closely associated with gout. Triglyceride-glucose body mass index (TyG-BMI), calculated from fasting triglyceride and fasting glucose, has recently been proposed as a surrogate indicator of insulin resistance, potentially offering a simplified method for assessing IR-related risk. The prevalence of gout in the U.S. is higher than in the rest of the world, and the condition is even worse in people with obesity and IR. Therefore, this study aims to explore the correlation of the new index with gout. In this cross-sectional study, 13,307 participants were enrolled from the NHANES database, spanning six survey periods from 2007 to 2008 to 2017–2018. Multivariable logistic regression was used to evaluate the association between TyG-BMI and gout in U.S. adults (> 20 years) and to estimate odds ratios. Restricted cubic spline (RCS) analysis and subgroup analysis were conducted to visualize the results and assess potential differences across specific subgroups. The fully adjusted multivariable logistic regression revealed that a 20-unit increase in TyG-BMI was linked to a 15% higher prevalence of gout (OR = 1.15; 95% CI: 1.11, 1.19). Compared with the lowest TyG-BMI tertile group, the participants in the highest showed a 169% higher prevalence of gout (OR = 2.69, 95% CI: 1.80, 4.00). This association remained consistent and robust across different models and subgroups. No significant interactions were observed between TyG-BMI and stratified variables. TyG-BMI is strongly associated with gout in U.S. adults, indicating the potential application of the new index as a supplementary tool in gout detection. More longitudinal studies are needed to confirm the causal relationship.