We first evaluated the baseline characteristics of patients for familial trait using chi-square and Wilcoxon’s rank-sum tests. Based on these results, we assessed the effect of family history of diabetes on two separate outcome measures: NASH and fibrosis (i.e., any fibrosis, and then advanced fibrosis, in separate models). Three multiple logistic regression models were run for each of the following outcomes: NASH (definite/borderline versus none), any fibrosis (grades 1-4 versus 0), and advanced fibrosis (grades 3 and 4 versus 0-2). All models included both family history of diabetes and personal

history of diabetes as covariates and the following covariates for adjustment: age at enrollment (years); gender (female versus male); BMI (kg/m2); ethnicity (Hispanic versus non-Hispanic); SB203580 research buy waist selleck screening library circumference (cm); Tg level (mg/dL); HDL level (mg/dL); systolic BP (mmHg); diastolic BP (mmHg); and blood glucose level (mg/dL). We then conducted sensitivity analyses by excluding

patients with personal history of diabetes and examined the association between family history of diabetes and presence of NASH and fibrosis on liver histology using the above-mentioned logistic regression models. We then utilized Wald’s test for interaction to assess whether there was a significant interaction between personal history of diabetes and family history of diabetes for these histological traits. Finally, joint effects of personal history of diabetes and family history of diabetes was examined using three separate logistic regression models to analyze the individual effects of personal history of diabetes and family history of diabetes,

as well as their combined effect on NASH and fibrosis. Individuals with no family history and personal history of diabetes were used as the control group for all three models. Age at enrollment, gender, and BMI were controlled for in these models. To determine whether the association between family history of diabetes and advanced histology in NAFLD is mediated by prediabetes, the cohort was further classified into prediabetic and normoglycemic participants. We conducted medchemexpress multivariate-adjusted logistic regression analyses to examine the association between family history of diabetes and risk of NASH and any fibrosis by adjusting for diabetes as well as prediabetes. In addition, we also examined whether prediabetes was independently associated with risk of NASH and any fibrosis in patients with NAFLD in similar models. All analyses were performed using SAS statistical software (version 9.2; SAS Institute Inc., Cary, NC). Nominal, two-sided P values were used and were considered to be statistically significant if P ≤ 0.05, a priori. This study included 1,069 patients from the NAFLD Database study and PIVENS trial. Mean age and BMI were 49.6 (± 11.8) years and 34.2 (± 6.4) kg/m2, respectively.