Methods: A total of 413 individuals (163 men and 250 women) aged 30-60 years were selected by stratified random sampling. The participants had safe alcohol consumption habits (<2 drinks/day) and no symptoms of hepatitis B and C. NAFLD was diagnosed through ultrasound. Blood pressure, anthropometric, and body composition measurements were made and liver function tests were conducted. Biochemical assessments, including the measurement of fasting blood sugar (FBS) and ferritin levels, as well as lipid profile tests were also performed. Metabolic syndrome was evaluated according to the International Diabetes Federation (IDF) criteria.
Results: The overall prevalence of ultrasound-diagnosed NAFLD was 39.3%. The results indicated a significantly higher prevalence of NAFLD in men than in women (42.3% vs 30.4%; P < 0.05). Binary logistic regression analysis was performed to determine the significant variables as NAFLD predictors. Overall, male gender, high body mass index (BMI), high alanine aminotransferase (ALT), high FBS, and high ferritin were identified as the predictors of NAFLD. The only significant predictors of NAFLD among men were high BMI and high FBS. These predictors were high BMI, high FBS, and high ferritin in women (P < 0.05 for all variables).
Conclusions: The metabolic profile can be used for predicting NAFLD among men and women. BMI, FBS, ALT, and ferritin are the efficient predictors of NAFLD and can be used for NAFLD screening before liver biopsy.
MATERIALS AND METHODS: In this cross-sectional study, the prevalence of NAFLD among 483 general adult populations was determined using ultrasonography. Anthropometric and biochemical variables were compared in groups with and without NAFLD and their predictive value for occurrence of NAFLD was investigated also.
RESULTS: Prevalence of NAFLD was 39.3%. Frequency of focal fatty infiltration (FFI), Grade I, Grade II, and Grade III of NAFLD was 9.5%, 21.1%, 7.2%, 1.4%, respectively. Prevalence of different types of NAFLD and FFI, was not different between female and male participants (P = 0.238). Ordinal regression was determined that all of the studied variables have significant predictive value for NAFLD (P < 0.001, γ = 0.615). Spearman correlation indicated that there was a significant relationship between NAFLD and BMI (r = 0.37, P < 0.001), age (r = 0.15, P = 0.001), FBS (r = 0.20, P < 0.001), cholesterol (r = 0.19, P < 0.001), triglyceride (r = 0.20, P < 0.001), LDL (r = 0.16, P < 0.001), AST (r = 0.17, P < 0.001), and ALT (r = 0.31, P < 0.001).
CONCLUSIONS: Considering the high prevalence of NAFLD specially its lower grades among Isfahani adult general population and their association with studied variables, it seems that interventional studies which target-related mentioned risk factors could reduce the overall occurrence of NAFLD.