Association of different adiposity indices with breast cancer incidence and all-cause mortality: a nationwide cohort study

Obesity is a well-established risk factor for breast cancer and mortality. However, the comparative predictive performance of various adiposity indices remains unclear. This study aimed to evaluate the associations of six adiposity indices with breast cancer incidence and all-cause mortality among American women. We analyzed data from 12,829 women aged 20–85 years who participated in the National Health and Nutrition Examination Survey (NHANES) cycles 2005–2016. Five adiposity indices were evaluated: relative fat mass (RFM), waist-to-height ratio (WHtR), a body shape index (ABSI), reciprocal ponderal index (RPI), and conicity index (CI). Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curves and subgroup analyses were performed. Dose-response relationship shows the relationship between different indicators and breast cancer. Sensitivity analysis is used to test the stability of results. 367 breast cancer cases were included in our study. During a median follow-up of 101.4 months, 1,132 deaths occurred. After multivariable adjustment, ABSI was significantly positively associated with breast cancer incidence (OR = 1.21, 95% CI: 1.02–1.44) and all-cause mortality (HR = 1.22, 95% CI: 1.12–1.34) in the overall population, with stronger associations in women aged ≥ 50 years. CI was also positively associated with mortality (HR = 1.12), while RFM, WHtR, and RPI showed inverse associations with breast cancer in the ≥ 50 years subgroup. ABSI achieved the highest AUC (0.606) for breast cancer prediction and demonstrated the most consistent dose-response patterns. Among the five adiposity indices evaluated, ABSI demonstrated the strongest and most consistent associations with both breast cancer incidence and all-cause mortality, with stable predictive value across age groups. Also, larger prospective cohort studies are needed to continue exploration in the future.