The Impact of Dietary Interventions on Metabolic Outcomes in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) and Comorbid Conditions, Including Obesity and Type 2 Diabetes.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a public health concern, linked with immune-metabolic dysfunction. While lifestyle and dietary modifications remain the cornerstone of MASLD management, the optimal dietary approach remains uncertain. This systematic review aims to investigate the impact of model dietary patterns on metabolic outcomes in patients with MASLD and evaluate their effects in individuals with coexisting metabolic conditions, such as obesity, metabolic syndrome, and type 2 diabetes mellitus (T2DM). To conduct the review, PubMed, Scopus, Google Scholar, Cochrane CENTRAL, and ClinicalTrials.gov databases were searched for Randomized Controlled Trials (RCTs) on the adult population, published between January 2019 and September 2024, following PRISMA principles. The quality of the included RCTs was assessed qualitatively based on study characteristics. The main findings of this review demonstrated that the use of interventions with dietary model based on Mediterranean diet (MED) and intermittent fasting (IF) approaches, such as alternative-day fasting (ADF) and time-restricted feeding regimens (TRF) may have potential in reducing body weight, BMI, and waist circumference, with additional benefits of improving glycemic control and reducing inflammation. The effects on hepatic functions, although limited, may be linked with reduced enzyme activity and liver stiffness. Additionally, the use of lacto-ovo-vegetarian diet (LOV-D) and the Dietary Approaches to Stop Hypertension (DASH) diet may offer additional health benefits, including blood pressure management. This review suggests that MED and IF-based strategies may reduce BW, improve glycemic control, and lower inflammation, with potential benefits for hepatic function. Further long-term studies are needed to confirm these effects and underlying mechanisms, which will allow for the optimization of protocols and ensure their safety in MASLD.