Abstract
BACKGROUND: The associations between LDH and non-alcoholic fatty liver disease (NAFLD), as well as advanced hepatic fibrosis (AHF), have not been explored. This study aims to investigate the association between log-transformed LDH levels and the prevalence of NAFLD and AHF. METHODS: In this cross-sectional study, after applying specific criteria for inclusion and exclusion, a total of 7,316 individuals were chosen from the 59,842 participants for the final analysis. LDH levels were measured using an enzymatic rate method. A fatty liver index (FLI) greater than or equal to 60 and an NAFLD fibrosis score (NFS) higher than 0.676 were found to be indicative of hepatic steatosis and advanced hepatic fibrosis. Both weighted multivariable linear and logistic regression analyses were used to finish the study. Moreover, additional analyses were performed utilizing weighted stratified analysis and weighted smoothed curve fitting using the generalized additive model (GAM). RESULTS: Following data analysis, the multivariable regression model 3 showed a significant association between the elevated log-transformed LDH levels and AHF (OR: 3.087, 95% CI: 1.378-6.915, P = 0.007). Furthermore, a modest association was observed between log-transformed LDH tertiles and FLI (β(Q2 vs. Q1) = 0.965, 95% CI: 0.014-1.916, P = 0.047). However, there was no evidence to prove that there was an association between log-transformed LDH levels and NAFLD in model 3. The weighted smoothed curve fitting using the GAM suggested a linear dose-response effect between log-transformed LDH levels and an increased risk of NAFLD, as well as a non-linear relationship between log-transformed LDH levels with AHF risk. Moreover, the weighted stratified analysis further suggested that the associations of log-transformed LDH with NAFLD and AHF could differ in different population groups. CONCLUSIONS: This study indicates that elevated log-transformed LDH levels are associated with an increased prevalence of AHF in our study population. However, the cross-sectional study analysis cannot prove causality, which requires further cohort studies or mechanistic studies to elucidate the precise mechanisms and root causes.