Food literacy and mindful eating are increasingly recognised as key factors in the prevention and management of chronic diseases, particularly type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). This study aimed to assess the association between food literacy and mindful eating and the risk of developing T2DM and MetS. This cross-sectional study included 1091 adults (777 females, 314 males) aged 18–65 years. General characteristics, anthropometric measurements, risk of T2DM (Finnish Diabetes Risk Score (FINDRISC)) and MetS (Metabolic Syndrome Index), food literacy (Food Literacy Tool) and mindful eating (Mindful Eating Inventory) were assessed using a questionnaire. Food literacy and mindful eating scores were significantly and negatively correlated with both the FINDRISC score ( r = −0·153 and r = −0·168, respectively; P < 0·001) and the Metabolic Syndrome Index score ( r = −0·181 and r = −0·171, respectively; P < 0·001). Linear regression analyses indicated that age, marital status, education level, BMI, waist circumference and total scores from the Food Literacy Tool and the Mindful Eating Inventory were significant predictors of the risk of T2DM (R ² = 0·580; P < 0·001) and MetS (R ² = 0·440; P < 0·001). Given the association between food literacy, mindful eating and the risk of T2DM and MetS, public health interventions should incorporate these factors. The long-term effects of such interventions should be evaluated, and their adaptability to different sociocultural contexts should be explored to support effective global prevention and management.

Pregnancy is associated with profound metabolic, hormonal, and immunological adaptations accompanied by dynamic alterations in maternal gut microbiota composition and function. Emerging evidence suggests that maternal diet is a major regulator of these microbiota-related changes and may influence maternal–fetal health through microbial metabolites and host signaling pathways. Fermented foods and functional dietary components, including prebiotics, probiotics, synbiotics, and polyphenols, have gained increasing attention because of their potential to modulate gut microbial diversity, intestinal barrier integrity, inflammatory responses, and metabolic homeostasis. Mechanistically, these effects are mediated through pathways involving short-chain fatty acids, G protein-coupled receptors, nuclear factor kappa B signaling, histone deacetylase inhibition, and immune cell regulation. Altered microbiota-associated signaling has been linked to gestational metabolic disorders such as obesity, gestational diabetes mellitus, and preeclampsia, as well as fetal immune and metabolic programming. Particular emphasis is placed on the maternal–infant microbiome axis, highlighting how maternal nutrition and microbiota-mediated signaling may influence microbial transmission, fetal programming, and early-life microbiome development. This review summarizes current evidence regarding pregnancy-associated gut microbiota alterations and discusses the molecular mechanisms through which fermented foods and functional nutrition may influence maternal and fetal health outcomes.

Malva sylvestris is a medicinal herb recognized for its abundant antioxidants and phenolic compounds, which play a key role in its beneficial health effects. The study optimized the ultrasound-assisted extraction (UAE) of phenolic compounds from Malva sylvestris leaves using response surface methodology (RSM). Extraction parameters including time (10–30 min), solvent-to-solid ratio (50–250 mL/g), and ethanol concentration (0–100%) were investigated. The highest total phenolic content (TPC: 260.404 ± 19.450 mg GAE/L) was obtained at 20 min, 250 mL/g, and 100% ethanol, while the highest antioxidant activity (AOA: 78.964 ± 0.564%) was achieved at 20 min, 50 mL/g, and 0% ethanol. The UAE process was optimized to maximize TPC and AOA under the following conditions: 100% ethanol, 250 mL/g solvent to solid ratio, 20 min extraction time, 50% ultrasonic power, and 45 °C. Under these conditions, the predicted TPC was 240.55 mg GAE/L, closely matching the experimental value of 242.47 ± 2.18 mg GAE/L (RMSE: 0.624). Similarly, the predicted AOA was 64.92%, while the experimental value was 63.66 ± 2.82% (RMSE: 0.771), confirming model accuracy.