AimThis study aims to understand the association between body roundness index (BRI) and female infertility prevalence. Infertility is a public health concern with significant implications for individuals’ well-being and rights.MethodsAll individuals who completed the National Health and Nutrition Examination Survey (NHANES) between 2013 and 2018 were initially included in this cross-sectional study. Following the screening, 2,777 eligible participants were selected for analysis from the original pool of 10,375 participants. Trained operators conducted anthropometric measurements, including height, weight, and waist circumference. The BRI was then calculated based on established research. Data from infertility status questionnaires were gathered from the NHANES database for all participants, with self-reported infertility serving as the study outcome. Multivariable logistic regression and restricted cubic splines (RCS) were employed to investigate the relationship between BRI and infertility. Subgroup analyses were also conducted to further explore the association between BRI and infertility.ResultsUpon analyzing the baseline characteristics of all women in the study, notable distinctions were identified in the clinical and demographic features between fertile and infertile women. Our investigation revealed a positive correlation between BRI and the likelihood of infertility in both weighted and unweighted multiple logistic regression models. Additionally, BRI exhibited a significant association with infertility in both continuous and categorical forms. Utilizing RCS curves, we noted a linear escalation in the prevalence of infertility with rising BRI values. Subgroup analyses provided further clarity on these observations.ConclusionOur study demonstrates a statistically significant positive correlation between BRI and the prevalence of infertility across diverse populations, suggesting potential implications for infertility prevention and treatment. Future prospective cohort studies will explore this association and understand the underlying mechanisms.