Nonalcoholic fatty liver disease (NAFLD) is an emerging cause of chronic liver diseases and a major health problem worldwide. Dietary patterns may play a critical role in controlling and preventing this disease, but the available evidence is scarce. The current study aims to ascertain the association of adherence to the Dietary Approach to Stop Hypertension (DASH) diet and Mediterranean diet (MeD) with nonalcoholic fatty liver disease (NAFLD) among Iranian adults of the Amol Cohort Study (AmolCS). In a cross-sectional analysis among 3220 adults (55.3% men), age ≥ 18 years (46.96 ± 14.67), we measured usual dietary intake with a validated food frequency questionnaire (FFQ) and then calculated dietary pattern scores for DASH and MeD. Sociodemographic and lifestyle factors were collected by a structured questionnaire. The presence and degree of NAFLD were also determined by abdominal sonography. Multiple regression models were used to estimate NAFLD odds across tertiles of DASH and Mediterranean dietary scores. Dietary DASH and Mediterranean components were adjusted for total energy intake, based on the residual methods. After adjusting for multiple potential confounders, we found an inverse association of DASH and MeD with NAFLD (Ptrend = 0.02, and Ptrend = 0.002, respectively). Those in the highest tertiles of adherence to the DASH and MeD had the lowest risk for NAFLD (OR = 0.80, 95%CI = 0.66–0.96, OR = 0.64, 95%CI = 0.52–0.78, respectively). The results of logistic analysis of MeD, stratified by gender and abdominal obesity, revealed the favorable association was more pronounced in women (OR = 0.42, 95%CI = 0.29–0.61, Ptrend = 0.004), and in participants with or without abdominal obesity (OR = 0.62, 95% CI = 0.47–0.81, Ptrend = 0.03, OR = 0.64, 95%CI = 0.475–0.91, Ptrend = 0.04, respectively). Similar results were obtained for the adherence to DASH diet score with the prevalence of NAFLD patients with abdominal obesity (OR = 0.75, 95% CI = 0.57–0.97, Ptrend = 0.04). The findings suggested the favorable association between DASH and MeD with NAFLD in Iranian adults, especially women and subjects with or without abdominal obesity. Further prospective investigations are needed to confirm the integrity of our findings.

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Considering the limited knowledge on the effects of dietary amino acid intake on dysglycemia, we assessed the possible association of dietary protein and amino acid patterns with the risk of pre-diabetes in a prospective population-based study. Participants without diabetes and pre-diabetes (n = 1878) were recruited from the Tehran Lipid and Glucose Study and were followed for a mean of 5.8 years. Their dietary protein and amino acid intakes were assessed at baseline (2006–2008); demographic, lifestyle, and biochemical variables were evaluated at baseline and in follow-up examinations. Pre-diabetes was defined according to the American Diabetes Association criteria. Multivariate Cox proportional hazard regression models, adjusted for potential confounders, were used to estimate the risk of pre-diabetes across tertiles of dietary protein and amino acid pattern scores. The mean age of the participants (44.9% men) was 38.3 ± 12.7 years at baseline. Three major amino acid patterns were characterized: (1) higher loads of lysine, methionine, valine, aspartic acids, tyrosine, threonine, isoleucine, leucine, alanine, histidine, and serine; (2) higher loads of glycine, cysteine, arginine, and tryptophan; and (3) higher loads of proline and glutamic acid. Dietary total protein intake Hazard Ratio (HR) = 1.13, 95% Confidence Interval (CI) = 0.92–1.38 and HR = 1.00, 95% CI = 0.81–1.23, in the second and third tertile, respectively) was not related to the development of pre-diabetes. The highest score of second dietary amino acid pattern tended to be associated with a decreased risk of pre-diabetes (HR = 0.81, 95% CI = 0.65–1.01), whereas the third pattern was related to an increased risk in the fully adjusted model (HR = 1.24, 95% CI = 1.02–1.52; p for trend = 0.05). These novel data suggest that the amino acid composition of an individual’s diet may modify their risk of pre-diabetes.