Utility of Six Novel Anthropometric Indicators for Assessing Metabolic Dysfunction-Associated Steatotic Liver Disease in US Reproductive-Aged Women: An NHANES Cross-Sectional Study

In recent years, novel anthropometric indices have been shown to improve the accuracy of body fat percentage estimation and are regarded as more effective in predicting their association with metabolic dysfunction-associated fatty liver disease (MAFLD); this study aimed to evaluate their effectiveness in risk assessment for metabolic dysfunction-associated steatotic liver disease (MASLD) among U.S. women of reproductive age. Utilizing data from the U.S. NHANES database (2017–2020 cycle), 1,060 women aged 20–44 years (of reproductive age) were enrolled, with a MASLD prevalence of 40.8% (433/1,060). Multivariate logistic regression, generalized additive models with smoothing curve fitting (for dose-response relationships), and receiver operating characteristic (ROC) curve analysis (to measure predictive ability) were employed;The fully adjusted multivariable logistic regression identified significant positive associations between MASLD and all six anthropometric indices: lnLAP (OR = 7.06, 95%CI = 5.12–9.73), WTI (OR = 6.84, 95%CI = 4.65–10.06), WWI (OR = 2.95, 95%CI = 2.34–3.72), ABSI (OR = 1.89, 95%CI = 1.34–2.67), WHTR (OR = 1.13, 95%CI = 1.11–1.16), BRI (OR = 1.69, 95%CI = 1.54–1.84). Dose-response analysis revealed a 48.91-fold increased MASLD risk (95%CI = 24.68–96.93) in the highest vs. lowest lnLAP quartile, with a significant risk threshold at the lnLAP = 2.34. ROC analysis demonstrated superior predictive performance for lnLAP (AUC = 0.85, 95%CI = 0.82–0.87), followed by WHTR and BRI (AUC = 0.84, 95%CI = 0.82–0.87), and moderate accuracy for WTI (AUC = 0.80, 95%CI = 0.77–0.82), Subgroup analysis indicated race significantly modified associations for WTI and ABSI.The novel anthropometric indices—particularly lnLAP—represent effective screening tools for MASLD in women of reproductive age. These findings provide a clinically applicable and cost-effective strategy for early risk stratification in this population, with notable implications for preventive care in primary health settings.