The combined impact of BMI and ABSI on all-cause mortality among American adults with diabetes.

Abstract

Objective: Previous studies have emphasized the independent effects of anthropometric indices-including body mass index (BMI), A Body Shape Index (ABSI), waist-to-height ratio (WHtR), body roundness index (BRI), and Conicity Index-on mortality. However, their combined impact, especially in diabetic populations with distinct obesity patterns, has been less frequently explored. This study investigates both the independent and combined effects of these anthropometric indices on mortality in diabetic Americans and compares their individual and combined diagnostic value.

Methods: A nationally representative cohort study was conducted using NHANES data (2005-2018), including 6,572 diabetic adults. Weighted Cox proportional hazards models and restricted cubic splines were applied to evaluate the independent and combined associations of anthropometric indices (BMI, ABSI, WHtR, BRI, and Conicity Index) with all-cause mortality. The weighted receiver operating characteristic (ROC) curve was used to assess the diagnostic value of individual anthropometric indices and their combinations in predicting mortality.

Results: Among all the anthropometric indices, ABSI exhibited the strongest independent association with all-cause mortality, outperforming other measures such as BMI, WHtR, BRI, and Conicity Index. A clear linear relationship was identified, with higher ABSI tertiles consistently linked to an increased risk of mortality. Notably, within each BMI tertile, ABSI effectively differentiated mortality risk, particularly in the highest tertile. Furthermore, ABSI demonstrated the highest predictive performance among individual metrics (weighted AUC = 0.653) and showed further improvement when combined with BMI (weighted AUC = 0.669).

Conclusion: BMI and ABSI collectively provide a comprehensive evaluation of mortality risk in diabetic populations, capturing the synergistic effects of general and central obesity. These findings highlight the importance of integrating BMI and ABSI into risk assessments to identify high-risk individuals and guide targeted interventions for reducing mortality.