Chinese Visceral Adipose Index Shows Superior Diagnostic Performance in Predicting the Risk of Metabolic Dysfunction...

Previous studies have reported the diagnostic values of multiple obesity indicators for predicting the risk of non-alcoholic fatty liver disease. However, the diagnostic values of obesity indicators for predicting the risk of metabolic dysfunction-associated fatty liver disease (MAFLD) in early postmenopausal women is still unknown. Therefore, this study investigated the predictive values of common obesity indices for estimating the risk of MAFLD in early postmenopausal Chinese women.

This study enrolled 2514 early postmenopausal women, aged between 45 and 55 years, who underwent abdominal ultrasonography examination at the Health examination center of the Huadong Sanatorium between June 2021 and December 2021. The values for six obesity indices, namely, body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body adiposity index (BAI), and Chinese visceral adiposity index (CVAI) were extracted from the medical records.

Our data showed that all the six obesity indices were significantly associated with the risk of MAFLD (P < 0.05) in the obese subjects and five obesity indices except for BAI were significantly associated with the risk of MAFLD (P < 0.05) in the lean subjects. The six obesity indices showed a linear relationship with the risk of MAFLD (all P-values > 0.05). The ORs for the obesity indices with the exception of BAI showed proportional increase with the risk of MAFLD in the lean subjects. CVAI was the strongest predictor of the risk of MAFLD in both lean (AUC=0.868) and overweight/obese subjects (AUC=0.704) among the early postmenopausal women.

This study demonstrated that all the obesity indices were associated with an increased risk of MAFLD in the obese subjects and five obesity indices except for BAI were associated with an increased risk of MAFLD in the lean subjects among the early postmenopausal women. CVAI showed the strongest predictive performance in estimating the risk of MAFLD among early menopausal women.