Abstract
BACKGROUND: Osteoarthritis (OA), the most prevalent joint disease and a leading cause of disability globally, has its disease burden inadequately captured by body mass index (BMI). As the sole quantified risk factor in current Global Burden of Disease estimates, BMI accounted for only 20% of OA burden. A critical limitation of BMI is its inability to distinguish fat distribution patterns, particularly abdominal adiposity, which is increasingly recognized as a key driver of metabolic and musculoskeletal pathologies. Herein, we hypothesize that anthropometric indicators reflecting central adiposity, such as average sagittal abdominal diameter (ASAD), may outperform BMI in predicting OA risk, especially when considering sex and age differences. METHODS: This cross-sectional study analyzed 27,791 National Health and Nutrition Examination Survey participants (1999-2023) with complete OA diagnosis, anthropometric, and metabolic data. Participants were stratified by sex and age (40-year cutoff). Multivariable logistic regression, adjusted for confounders, estimated predictor-OA associations via standardized odds ratios (sORs), and these associations were evaluated by the area under the receiver operating characteristic curve (AUROC). Data were split into training (70%) and validation (30%) sets, with DeLong's test comparing different predictors against BMI. RESULTS: In the overall population, ASAD showed a stronger association with OA (sOR = 1.483) than BMI (sOR = 1.436), with comparable validation AUROC (ASAD: 0.857; BMI: 0.854). Sex-stratified analysis revealed that BMI was the optimal predictor for males (sOR = 1.466; validation AUROC = 0.844), while ASAD outperformed BMI in females (sOR = 1.486 vs. 1.450; validation AUROC = 0.865 vs. 0.863). Further age stratification revealed that in males under 40, both BMI (sOR = 1.261; validation AUROC = 0.750) and ASAD (sOR = 1.194; validation AUROC = 0.889) were the strongest predictors, and that ASAD (sOR = 1.490; validation AUROC = 0.769) and BMI (sOR = 1.482; validation AUROC = 0.736) remained strong for males aged 40 and above. In age-stratified analyses of females, ASAD showed the strongest consistent association with OA risk, both in participants under 40 (sOR = 1.472; validation AUROC = 0.801) and those aged 40 and above (sOR = 1.421; validation AUROC = 0.764). CONCLUSIONS: ASAD emerges as a superior predictor for females and a competitive population-level complement to BMI. BMI remains an optimal OA predictor for males. Within the National Health and Nutrition Examination Survey framework, these findings underscore the necessity of integrating abdominal adiposity metrics, particularly ASAD, into OA risk assessment to improve sex-specific prevention strategies.