Association of body roundness index with prostate cancer: a population-based cross-sectional study using NHANES data.

Background: Prostate cancer (PCa) is the second most common cancer worldwide and a major cause of cancer-related mortality. Although obesity is an established modifiable risk factor for multiple cancer types, conventional anthropometric measures such as body mass index (BMI) fail to capture body fat distribution, particularly visceral adiposity, which is thought to be strongly associated with carcinogenesis. The body roundness index (BRI) is a novel anthropometric metric that provides a more accurate estimation of percent body fat and visceral adipose tissue (VAT) than traditional indices. However, the association between BRI and PCa risk remains unclear in general population-based studies. Therefore, this study aimed to explore the relationship between BRI and PCa. Methods: Data from 18,732 male participants (aged ≥20 years) in the 1999-2018 National Health and Nutrition Examination Survey (NHANES) were analyzed. Participants with missing data on PCa status, BRI, or the covariates were excluded. PCa was defined based on self-reported physician diagnosis. BRI was calculated using validated anthropometric formulas. Multivariable logistic regression models assessed the BRI-PCa relationship, adjusting for age, race, education level, marital status, poverty income ratio (PIR), BMI, alcohol use, smoke, hypertension, diabetes, coronary heart disease, stroke, total cholesterol, high-density lipoprotein cholesterol. Restricted cubic spline (RCS) and subgroup analyses evaluated nonlinearity and interaction effects. Receiver operating characteristic (ROC) curves compared BRI's predictive performance against BMI, waist circumference, and weight. Results: A higher BRI was significantly associated with increased PCa risk. In fully adjusted models, each 1-unit increase in BRI raised PCa odds by 17% [odds ratio (OR) =1.17, 95% confidence interval (95% CI): 1.06-1.28, P<0.001]. Individuals in the highest BRI quartile exhibited a PCa risk that was four-fold higher than those in the lowest quartile (OR =4.00, 95% CI: 2.32-6.90, P<0.001). RCS analysis revealed a nonlinear positive correlation. Subgroup analyses confirmed consistent associations in all subgroups. Compared with BMI [area under the curve (AUC) =0.509, 95% CI: 0.486-0.533], waist circumference (AUC =0.594, 95% CI: 0.572-0.615) and body weight (AUC =0.488, 95% CI: 0.465-0.512), BRI showed a moderate and significant improvement in the discriminative ability of PCa (AUC =0.608, 95% CI: 0.587-0.630) (P<0.001). Conclusions: Among the general population in the United States, BRI is independently and positively correlated with the risk of PCa. BRI showed modest but significant improvement in PCa risk discrimination compared to traditional obesity indicators, suggesting its potential as a complementary anthropometric tool that merits validation in prospective studies with clinical endpoints.