Epidemiology of metabolic dysfunction-associated steatotic liver disease and discordance in non-invasive fibrosis scores in Eastern China: A cross-sectional study

The contemporary epidemiology of metabolic dysfunction-associated steatotic liver disease (MASLD) and the risk stratification provided by noninvasive tests (NITs) for fibrosis in large populations require further characterization. Specifically, the degree of agreement between different NITs and how their association with metabolic comorbidities varies in Chinese MASLD cohorts remains unclear. This study aimed to systematically evaluate the prevalence of MASLD and to compare the performances among 3 NITs for fibrosis in a large eastern Chinese cohort. In this cross-sectional study, which included 201,616 adults from eastern China between January 01, 2021 and March 31, 2025, MASLD was diagnosed based on hepatic steatosis on ultrasonography plus metabolic criteria according to the latest guidelines. Liver fibrosis was assessed using the FIB-4 index, nonalcoholic fatty liver disease fibrosis score (NFS), and aspartate transaminase to platelet ratio index (APRI). Sex-and age-standardized prevalence was calculated. Associated factors were analyzed via multivariable logistic regression. The standardized prevalence of MASLD was 39.42%, higher in males (49.98%) than females (28.59%), with obesity as the strongest risk factor (aOR: 7.69). Among MASLD patients, significant fibrosis prevalence was similar when assessed by FIB-4 (19.12%) and NFS (21.32%); advanced fibrosis was lowest according to APRI (0.61%) compared to FIB-4 (1.79%) and NFS (1.97%). Critically, the associations between metabolic comorbidities (e.g., diabetes, dyslipidemia) and fibrosis risk varied substantially depending on the NIT used. MASLD is highly prevalent in this eastern Chinese health checkup cohort. The marked discordance in fibrosis risk stratification across different NITs, particularly in patients with metabolic comorbidities, highlights that these tools provide complementary rather than interchangeable information. These findings suggest the need for cautious interpretation of NIT results and further research into context-aware risk stratification strategies that consider both the specific NIT employed and the patient’s metabolic profile.