Non-linear associations of a body shape index with diabetes among adults: A cross-sectional study

Objective: This study aimed to explore the relationship between a body shape index (ABSI) and diabetes, and to assess the robustness of this relationship across different population subgroups. Methods: Utilizing data from the National Health and Nutrition Examination Survey (NHANES) database, this study employed multivariate linear regression analysis to evaluate the association between ABSI and the likelihood of having diabetes. This research further explored non-linear issues in gender stratification through smooth curve fitting and two-part linear regression models, analyzing different subgroups including gender, race, hypertension, and stroke. Results: A total of 34,693 participants were involved in the study, with a diabetes prevalence of 11.60%. The prevalence increased with higher tertiles of ABSI. After comprehensive adjustment, ABSI was positively correlated with diabetes (OR = 1.42, 95% CI: 1.33, 1.52). Participants in the highest quartile of ABSI had a 96% higher odds of having diabetes (OR = 1.96, 95% CI: 1.69, 2.26), than did those in the lowest quartile. Smooth curve fitting analysis revealed a non-linear, inverse L-shaped relationship between ABSI and diabetes, with a breakpoint at 9.54. Subgroup analyses indicated that the association between ABSI and diabetes remained stable across different populations, except for those with a history of stroke. Conclusion: Our findings suggest that there is a positive correlation between diabetes and increased ABSI. ABSI may serve as an effective alternative indicator to other obesity indices, such as BMI.