Goals: To compare current nonalcoholic fatty liver disease (NAFLD)-related algorithms to find suitable algorithms for NAFLD, especially lean NAFLD in middle-aged and elderly Chinese population.
Background: NAFLD is the most common cause of chronic liver disease in the world today. Various algorithms based on obesity indicators, blood lipids, and liver enzymes, etc. have been developed to screen NAFLD.
Materials and methods: General, anthropometric and biochemical characteristics were collected. One-way analysis of variance and the χ test were applied to test the differences in continuous and categorical variables, respectively. Multivariable logistic regression analyses, adjusted by age, gender, body mass index, tobacco use, alcohol consumption, and physical activities, were used to investigate the associations between NAFLD-related algorithms and NAFLD. The accuracy and cut-off point of NAFLD-related algorithms to detect NAFLD were evaluated by area under the receiver operator characteristic curve and the maximum Youden index analysis, respectively.
Results: In 8 NAFLD-related algorithms, the receiver operator characteristic of fatty liver index (FLI) and waist circumstance-to-height ratio (WHR) for NAFLD were in the whole (0.83 and 0.84), lean (0.74 and 0.74), and overweight/obese (0.71 and 0.72) population, respectively, which were higher than those of other algorithms. The cut-off points of WHR and FLI for NAFLD were different in the overall (0.50 and 20), lean (0.47 and 10), and overweight/obese (0.53 and 45) population.
Conclusions: WHR and FLI could be the most accurate of 8 algorithms for the noninvasive diagnosis of NAFLD in both lean and overweight/obese population.