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Öğe Are hedonic hunger and health-related quality of life associated with obesity in adolescents?(Frontiers Media Sa, 2025) Koc, Bilge Meral; Kenger, Emre Batuhan; Yuksel, Ezgi Arslan; Karahan, Tugce OzluThe purpose of the study is to find out the relationship between obesity, hedonic hunger and health-related quality of life (HRQoL). The questionnaire containing items on the sociodemographic characteristics, anthropometric measurements and nutritional habits of individuals (n = 902), the Children's Power of Food Scale and the KIDSCREEN-10 were used to determine the hedonic hunger and the HRQoL score. Hedonic hunger and HRQoL were evaluated according to the categories, frequency of consumption of sugary drinks and fast food. The females were found to have hedonic hunger more than the males (p < 0.05). Body mass index z-score categories of the adolescents showed that the obese eat more hedonically compared to the underweight and the normal-weight (p < 0.05), and this difference was not observed in the HRQoL scores (p > 0.05). There was a negative correlation between the hedonic hunger status and the HRQoL scores (R = -0.342, p = 0.000). The consumption of sugary drinks and fast food was associated with hedonic hunger and HRQoL scores in certain groups. Hedonic hunger is associated with obesity; hedonic hunger and quality of life are important factors associated with unhealthy food and drink intake.Öğe Artificial Intelligence-Based Diets: A Role in the Nutritional Treatment of Metabolic Dysfunction-Associated Steatotic Liver Disease?(Wiley, 2025) Karahan, Tugce Ozlu; Kenger, Emre Batuhan; Yilmaz, YusufBackground: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health concern. Effective management of this condition relies heavily on lifestyle modifications and dietary interventions. In this study, we sought to evaluate the dietary plans for MASLD generated by ChatGPT (GPT-4o) according to current guideline recommendations. Methods: ChatGPT was used to create single-day meal plans for 48 simulated patients with MASLD, tailored to individual characteristics such as age, gender, height, weight and transient elastography parameters. The plans were assessed for appropriateness according to disease-specific guidelines. Results: The mean energy content of the menus planned by ChatGPT was 1596.9 +/- 141.5 kcal with a mean accuracy of 91.3 +/- 11.0%, and fibre content was 22.0 +/- 0.6 g with a mean accuracy of 88.1 +/- 2.5%. However, they exhibited elevated levels of protein, fat and saturated fat acids. Conversely, the carbohydrate content was lower. ChatGPT recommended weight loss for obese patients but did not extend this advice to normal-weight and overweight individuals. Notably, recommendations for a Mediterranean diet and physical activity were absent. Conclusions: ChatGPT shows potential in developing dietary plans for MASLD management. However, discrepancies in macronutrient distributions and the omission of key evidence-based recommendations highlight the need for further refinement. To enhance the effectiveness of AI tools in dietary recommendations, alignment with established guidelines must be improved.Öğe Artificial Intelligence-Generated Diet Plans for Hypertension and Dyslipidemia: Adherence and Nutritional Insights(Iranian Scientific Society Medical Entomology, 2025) Kenger, Emre Batuhan; Karahan, Tugce OzluBackground: We evaluated diet plans generated by ChatGPT for hypertension and dyslipidaemia. Methods: In October 2024, ChatGPT was used to generate meal plans for 24 simulated patients with different cardiovascular health problems. Data were used from men (n=12) and women (n=12), aged 56 yr, with mean heights of 176 cm and 161 cm respectively. Weight categories were based on BMI: normal, overweight, and obese, using weights of 56, 71, and 84 kg for women and 67, 85, and 101 kg for men. Four health conditions were assessed: hypertension stages 1 and 2 (systolic BP 130-139 mm Hg and >= 140 mm Hg; diastolic BP 80-89 mm Hg and >= 90 mm Hg), and elevated LDL levels (>= 130 mg/dL and >= 160 mg/dL). Menus were evaluated for adherence to Mediterranean and DASH diets, including recommendations. Results: Adherence to the Mediterranean and DASH diets was low across all groups, with median scores below 9 and 4.5, respectively. Common recommendations included weight loss, physical activity, reduced salt intake, stress management, and omega-3s for both hypertension and LDL reduction. Plant sterols/stanols were suggested only for LDL. No advice was given on smoking or alcohol use. Nutrient content did not differ significantly between hypertension and LDL menus (P>0.05). Conclusion: This pioneering study found that AI-generated dietary models had low adherence to DASH and Mediterranean diets, though most recommendations were generally appropriate. Since the prompts only requested basic nutrition plans, future research should use more specific, personalized prompts to better assess AI's role in managing chronic diseases.Öğe Body Appreciation is Associated with Emotional Eating in Turkish Female Athletes(Georg Thieme Verlag Kg, 2024) Kenger, Emre Batuhan; Karahan, Tugce OzluIt is known that female athletes are at risk for eating disorders. It is thought that factors such as pressure and stress experienced by professional athletes may affect emotional eating and body appreciation. In this context, the aim of this study was to evaluate the emotional eating and body appreciation of professional Turkish female athletes. A total of 265 professional female athletes were categorized according to their sport types and nationality. Emotional eating was found to be higher and body appreciation to be lower in athletes competing at the national level. The results of the hierarchical regression analysis, which included variables such as age, body mass index, professional sports background, national level, and sport type show that the most effective factor in explaining emotional eating in professional female athletes is body appreciation. The present study findings support that professional female athletes are at risk in terms of emotional eating and body appreciation. In addition, emotional eating scores were found to be higher and body appreciation scores were lower in national athletes. Psychological factors such as intense stress and pressure have an impact on the eating behavior and body appreciation of national athletes. These results suggest that athletes should be evaluated by nutritionists, doctors, and psychologists from a multidisciplinary perspective.Öğe ChatGPT-4o for Weight Management: Comparison of Different Diet Models(Wiley, 2025) Karahan, Tugce Ozlu; Kenger, Emre BatuhanIn recent years, artificial intelligence (AI) tools such as ChatGPT have emerged as accessible and scalable platforms for generating dietary advice. While ChatGPT has demonstrated potential in providing general nutritional guidance, its capacity to create diet plans tailored to different weight categories and physical activity levels remains underexplored, particularly in comparison across popular dietary (ketogenic and intermittent fasting) models. This study aimed to evaluate the nutritional adequacy and variability of diet plans generated by ChatGPT-4o for weight management. ChatGPT-4o generated diet plans for 18 individuals (9 males, 9 females) representing overweight, class I, and class II obesity at varying physical activity levels. Fifty-four menus were created across three dietary models and analyzed for energy, macro-, and micronutrient content using the BeBiS nutritional analysis software. Diet variability was also assessed through repeated prompts over three different periods. The ketogenic diets produced by AI had significantly higher energy and saturated fat contents than other models (p < 0.05). Regardless of prompt, AI often produced low-carbohydrate, high-fat diets. The menus created by ChatGPT had significantly higher fat, saturated fat, and protein content but lower carbohydrate content compared to the dietitian menus (p < 0.05). Micronutrient analysis showed frequent inadequacy in calcium, potassium, and vitamin B1. Notably, menu content showed temporal inconsistencies, particularly in intermittent fasting and ketogenic diets. While ChatGPT-4o shows promise in generating basic dietary models, concerns remain about its nutritional precision, consistency, and safety. The results revealed the necessity of professional supervision in AI-assisted nutrition planning.Öğe Complementary feeding practices and nutritional status in infants living in Turkey: Iowa infant feeding attitude scale and complementary feeding index(Wiley, 2025) Koc, Bilge Meral; Karahan, Tugce Ozlu; Yuksel, Ezgi Arslan; Garipoglu, GokcenAlthough complementary feeding (CF) and maternal attitudes towards infant feeding are known to affect the nutritional status of infants during the neonatal period, studies in this field remain limited. The present study aimed to determine CF practices for infants aged 6-12 months who live in Turkey and maternal attitudes towards infant feeding. In addition, the effects of CF practices and maternal attitudes on the nutritional status of infants were examined. This study included 720 infants, of whom 289 were aged 6-8 months and 431 were aged 9-12 months. CF status was assessed using the CF index (CFI), and maternal attitudes towards infant feeding were measured using the Iowa infant feeding attitude scale (IIFAS). The weight and length measurements of infants were categorized using z-scores. Infants with weight-for-age z-score (WAZ) and weight-for-length z-score (WLZ) of less than -2 standard deviation were categorized as malnourished. Mothers of malnourished infants were found to have lower CFI and IIFAS scores (p < 0.05). Consistency of fruit feeding and complementary foods in the first 3 days of CF was associated with WAZ. The mothers' level of knowledge about CF and appropriate CF practices significantly affects the nutritional status of infants. The tools used in the present study to monitor CF practices should be incorporated into public health programmes.Öğe Effects of Intermittent Fasting on Liver Steatosis and Fibrosis, Serum FGF-21 and Autophagy Markers in Metabolic Dysfunction-Associated Fatty Liver Disease: A Randomized Controlled Trial(Mdpi, 2025) Karahan, Tugce Ozlu; Akyuz, Elvan Yilmaz; Karadag, Demet Yilmaz; Yilmaz, Yusuf; Eren, FatihBackground: This randomized controlled study sought to determine the effect of intermittent fasting on anthropometric measurements, fibroblast growth factor (FGF)-21, and autophagy markers, as well as on hepatic steatosis and fibrosis levels in overweight or obese patients with metabolic dysfunction-associated fatty liver disease (MAFLD). Methods: Patients were randomly assigned into two groups: received a dietary treatment involving 22-25 kcal/kg/day of energy for 8 weeks and followed the same dietary intervention and a 16:8 pattern. The extent of hepatic steatosis and fibrosis was determined using transient elastography on a FibroScan (R) device. The controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), determined by transient elastography, reflect hepatic steatosis and fibrosis, respectively. In duplicate, serum levels of FGF-21, Beclin-1, and ATG-5 were determined using enzyme-linked immunosorbent assay. Results: The study included 48 patients with a mean age of 48.2 +/- 1.4 years (27 female and 21 male). Improvements in anthropometric measurement and CAP and LSM levels and a decrease in serum FGF-21 levels were found in both groups (p < 0.05). Changes in the CAP and FGF-21 levels were higher in the energy + time-restricted diet group (p < 0.05). Autophagy-related protein (ATG)-5 levels increased only in the energy + time-restricted diet group [(0.74 (0.46-1.29) ng/mL vs. 0.95 (0.73-1.32) ng/mL, p = 0.03]. Conclusions: Intermittent fasting was potentially practical in the management of MAFLD. In particular, changes in FGF-21 and ATG-5 levels indicate the potential of intermittent fasting to regulate metabolic processes and autophagy. However, methodological limitations should be taken into consideration when interpreting the study results.Öğe Guideline Compliance of Artificial Intelligence-Generated Diet Plans After Bariatric Surgery: A Cross-Sectional Simulation Comparing ChatGPT-4o, DeepSeek and Grok-3(Mdpi, 2025) Yilmaz, Aylin Bolat; Kenger, Emre Batuhan; Karahan, Tugce Ozlu; Saglam, Duygu; Bas, MuratBackground/Objectives: Artificial intelligence (AI)-based tools are increasingly being used in tailored nutrition management, and evaluating their compliance with guidelines is significant in clinically sensitive areas, including bariatric surgery. This study aimed to investigate the extent to which diet plans recommended by AI models in the early period following sleeve gastrectomy (SG) align with current clinical nutrition guidelines (ASMBS, AACE/TOS). Methods: A total of 360 menu plans were generated using three AI platforms-ChatGPT-4o, DeepSeek V3, and Grok-3-for 40 simulated patients (20 females, 20 males; BMI 32-45 kg/m2) across three postoperative stages: liquid (day 5), puree (day 16), and solid (day 35). The energy and nutrient contents of the menus were analyzed using BeBiS 8.1; an experienced dietitian assessed compliance with the guidelines using a structured checklist. Nutrient intakes and guideline compliance scores were examined using within-patient Friedman tests followed by Bonferroni-adjusted pairwise comparisons. Results: ChatGPT-4o demonstrated the highest overall compliance scores, particularly in the liquid and pur & eacute;ed phases, while DeepSeek produced higher values for several micronutrients. All models showed substantial gaps in essential postoperative recommendations, most notably thiamine and multivitamin supplementation. Conclusions: Although LLMs can generate partially guideline-concordant postoperative diet plans, they consistently omit several critical elements of bariatric nutrition care. These findings indicate that LLM-generated menus may serve as supportive educational tools, and diet planning must be performed under the guidance of a specialist dietitian. This simulation does not assess clinical safety, efficacy, or patient outcomes and should not be used as a substitute for dietitian-led postoperative nutrition care.Öğe Planet-friendly plates: the effect of a plant-based diet on sustainable eating behavior in a sample of Turkish adults(Wiley, 2025) Kenger, Emre Batuhan; Karahan, Tugce Ozlu; Koc, Bilge MeralBackground: In addition to the health effects of plant-based diets, their impact on the environment is becoming increasingly important. This study was conducted to assess the impact of adherence to a plant-based diet on sustainable eating behaviors. Materials and methods: This cross-sectional study was conducted on 2122 Turkish adults, 73% female and 27% male. The plant-based diet index (PDI), healthy plant-based diet index (hPDI) and unhealthy plant-based diet index (uPDI) were obtained from a validated semi-quantitative food frequency questionnaire (FFQ). After the index scores were calculated, the sample was divided into tertiles for each index. The sustainable eating behaviors of the participants were determined with the 'Behaviors Scale towards Sustainable Nutrition'. Results: The PDI and hPDI levels of female participants were found to be higher than those of male participants. Factors such as age, exercise and educational status were also found to affect adherence to a plant-based diet. In regression models, PDI (Model 1; beta: 0.413, Model 2; beta: 0.369, Model 3; beta: 0.367) and hPDI (Model 1; beta: 0.462, Model 2; beta: 0.366, Model 3; beta: 0. 351) scores had a positive effect on sustainable eating behavior scores, whereas uPDI (Model 1; beta: -0.496, Model 2; beta: -0.471, Model 3; beta: -0.459) scores had a negative effect (P < 0.001). Conclusion: Our findings suggest that individuals with higher adherence to overall plant-based and healthy plant-based diets exhibit more sustainable eating behaviors. Promoting healthy plant-based diets presents a promising approach to advancing sustainable nutrition, and mitigating environmental challenges. (c) 2024 Society of Chemical Industry.
