In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social media and spend an average of 2.2 h a day on these platforms. At the same time, artificial intelligence (AI) applications have become widespread in many fields, such as health, education, and finance. While AI has the potential to monitor eating behaviors and provide personalized health support, excessive use of social media and AI can lead to negative effects. These include addiction and reduced quality of life. It is important to examine the attitude toward AI and its relationship with social media addiction, eating behavior, and life satisfaction. Research on the connection between AI attitudes and eating habits is lacking, which emphasizes the necessity of validating AIAS-4 in Turkish in order to ensure its efficacy in this context. The first stage of the study aimed to adapt Grassini’s (2023) Artificial Intelligence Attitude Scale (AIAS-4) into Turkish and assess its validity and reliability. In the second stage, it was aimed to examine the relationship between artificial intelligence attitude and social media addiction, eating behavior, and life satisfaction. This study cross-sectional and methodological study was conducted in two stages in Türkiye. 172 adult individuals underwent a validity and reliability study in the first stage (43% of them were men and 57% were women), which involved adapting the AIAS-4 into Turkish. In the second stage, the relationships between artificial intelligence attitude, social media addiction, eating behavior, and life satisfaction of 510 individuals were evaluated with an average age of 24.88 ± 7.05 years (30.8% male, 69.2% female). Using the snowball sampling technique, the survey was carried out on adults by reaching out to staff and their families from both universities (Gazi University and Tokat Gaziosmanpaşa University) as well as students and their relatives. A face-to-face survey approach (delivered by an interviewer) was used for the study. In this study, the Social Media Addiction Scale-Adult Form(SMAS-AF) was used to assess social media addiction, the Scale of Effects of Social Media on Eating Behavior (SESMEB) was used to measure the impact of social media on eating behavior, the Contentment with Life Assessment Scale was used to evaluate life satisfaction, and the Eating Disorder Examination Questionnaire (EDE-Q total) was used to assess eating disorder symptoms. Pearson Correlation and Spearman Correlation according to normality and Linear regression analysis were used to analyse variables. AIAS-4 was a valid and reliable instrument in this study conducted in Türkiye (Cronbach’s alpha = 0.90 and McDonald’s omega = 0.89). Individuals spend an average of 3.7 ± 1.99 h per day on social media. All participants used WhatsApp, while 89.8% used Instagram. A negative correlation was found between AIAS and EDE-Q total, (r=-0.119 p < 0.05). BMI correlated positively with EDE-Q total (r = 0.391, p < 0.01). Higher AIAS scores were associated with increased time spent on social media (r = 0.129, p < 0.001). Conversely, higher AIAS scores were associated with lower EDE-Q total scores (r= -0.119, p < 0.001). SESMEB correlated positively with EDE-Q total (r = 0.169; p < 0.001). The model showed that BMI (β = 0.311; p < 0.001), AIAS (β =-0.157, p = 0.005), SMAS-AF (β = 0.036; p = 0.002) and SESMEB (β = 0.022; p = 0.038) affected EDE-Q total (p < 0.001 R2 = 0.198). This study revealed that the Artificial Intelligence Attitude Scale (AIAS) is valid and reliable for Turkish adults. The results show that BMI, social media addiction have positive, and AI attitude has negative impact on eating behaviors. These findings emphasize the importance of multidisciplinary approaches and awareness programs in the prevention and management of eating disorders.

The effect of diet on sleep quality has been addressed in many studies; however, whether/how plant-based diets (PBDs) impact sleep-related parameters has not been explored in detail. This review aims to give an overview of the components of PBDs and the possible mechanisms through which PBDs may improve sleep quality. Studies have indicated that diets such as PBDs, which are typically high in fruits, vegetables, nuts, seeds, whole grains, and fiber, are associated with better sleep outcomes, including less fragmented sleep and improved sleep duration. Several mechanisms may explain how PBDs impact and/or improve sleep outcomes. Firstly, PBDs are characteristically rich in certain nutrients, such as magnesium and vitamin B6, which have been associated with improved sleep patterns. Secondly, PBDs are often lower in saturated fats and higher in fiber, which may contribute to better overall health, including sleep quality. Additionally, plant bioactive compounds like phytochemicals and antioxidants in fruits, vegetables, and herbs may have sleep-promoting effects. According to available data, PBD and Mediterranean diet elements promise to enhance sleep quality; however, it is crucial to note that diets should be customized based on each person’s needs.

Lactic acid bacteria (LAB) are a group of microorganisms which are beneficial and well-characterized with respect to the flavor and texture of food products via fermentation. The accumulated literature has suggested that dietary intake of fermented foods rich in LAB is related to different health-promoting benefits; however, in recent years, emerging evidence suggests a contribution of LAB to blood lipid regulation and cardiovascular health via certain mechanisms. Different potential mechanisms for the lipid regulatory effects of LAB may include the interaction of hydroxymethylglutaryl-CoA (HMG-CoA) reductase and bile salt hydrolase activity and bile salt metabolism; gut microbiome modulation; and regulation of mRNA expression of genes related to fat metabolism in animal models and human studies. This review comprehensively aims to answer whether/how LAB influence blood lipids in both animal models and human studies while also uncovering the underlying mechanisms linking LAB to lipid metabolism.

Background and Objectives: The global rise in obesity presents a significant public health challenge, with Turkey exhibiting one of the highest obesity rates in Europe. Body image dissatisfaction (BID) and lower food literacy (FL) have been associated with obesity, yet their interplay remains underexplored. This study aimed to investigate the relationship between body mass index (BMI), body image dissatisfaction, and FL in adults in Turkey. Materials and Methods: In total, 759 women and 419 men aged 18–64 years old were included in this study. The mean age was 31.34 ± 11.92. A total of 1178 participants completed an online questionnaire assessing anthropometric measurements, BID, using the Stunkard Figure Rating Scale, and FL, using a validated questionnaire. The data were analyzed using descriptive statistics, correlation analysis, and mediation analysis to explore the relationships between variables in SPSS 24.0. Results: Women desired to be thinner more frequently than men, and those with negative BID were predominantly individuals with overweight or obesity. Moreover, those with higher FL scores were more likely to be satisfied with their bodies. Correlation analysis demonstrated a negative relationship between BMI and FL (r = −0.94; p = 0.001) and a positive relationship between BMI and BID (r = 0.628; p < 0.001). Mediation analysis revealed that FL mediated the relationship between BID and BMI (β = −2.281; lower limit = −3.334, upper limit = −1.228). Conclusions: The findings highlight the importance of addressing BID and enhancing FL to mitigate obesity risk factors. This study contributes to understanding the complex interplay between BID, FL, and obesity, providing insights for public health interventions aimed at obesity prevention and management.

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.

Background: This cross-sectional study aimed to examine the associations between premenstrual syndrome–related quality of life (PMS-QoL), ultra-processed food (UPF) consumption, mindful eating, well-being, and social media addiction (SMA) among women. Methods: This study was conducted with 1,741 women aged 18–49 years (mean age: 24.86 ± 8.4). Data were collected via a web-based survey distributed through social media using snowball sampling. Premenstrual Syndrome Quality of Life Scale (PMS-QoL), Screening Questionnaire of Highly Processed Food Consumption (sQ-HPF), Mindful Eating Inventory (MEI), WHO-5 Well-Being Index (WHO-5), and Social Media Addiction Scale (SMAS) were used. Results: PMS-QoL was significantly correlated with social media addiction SMAS (r =-0.448,p < 0.001), sQ-HPF (r=-0.196, p < 0.001), and well-being (WHO-5)(r = 0.129, p < 0.001). MEI was positively correlated with WHO-5 (r = 0.179, p < 0.001) and age (r = 0.145, p < 0.001), and negatively correlated with SMAS (r = -0.100, p < 0.001), sQ-HPF (r =-0.086, p < 0.001), and BMI (r =-0.160, p < 0.001). In addition, sQ-HPF was positively correlated with SMAS (r = 0.208, p < 0.001).Linear regression analyses showed that PMS-QoL was significantly associated with BMI, sQ-HPF, SMAS, and WHO-5; (p < 0.001), while MEI was significantly associated with age, BMI, social media usage time, sQ-HPF, and WHO-5 (p < 0.001). Conclusion: This study highlights the multidimensional associations between PMS-related quality of life, eating behaviors, psychological well-being, and social media addiction. Higher UPF consumption and greater social media addiction were associated with poorer PMS-related quality of life, whereas mindful eating and higher well-being showed more favorable associations. From a women’s health perspective, these findings may point to the relevance of lifestyle-oriented and preventive approaches in relation to PMS-related quality of life.