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    Adult's food label awareness: scale development and validation
    (Emerald Group Publishing Ltd, 2026) Acikgoz, Inci; Kokturk, Seda Nur; Yardimci, Hulya
    PurposeThis study aimed to develop and validate the Food Label Awareness Scale (FLAS) to comprehensively assess adults' food label reading habits and expectations.Design/methodology/approachThe FLAS was developed based on a literature review and expert input. Initial item generation was followed by expert evaluations for content and face validity. Data were collected through structured face-to-face interviews using the preliminary version of the FLAS and a sociodemographic questionnaire. A total of 300 adults aged 20-65 years participated. Food label awareness was assessed based on the three subdimensions: (1) product packaging and ingredients, (2) nutrition and health and (3) product brand. In addition, participants' age, gender and education level were recorded. Cronbach's alpha assessed internal consistency. Reliability was supported by comparing the highest and lowest 27% of total scores. Associations between demographics and subdimension scores were tested using appropriate statistical methods.FindingsThe finalized 18-item FLAS demonstrated a three-factor structure with acceptable model fit and internal consistency. Older adults had higher awareness of packaging and ingredients. Lower education was associated with greater reliance on product brand.Research limitations/implicationsA primary limitation is the geographically restricted sample, which may limit the generalizability of the findings.Originality/valueThis study is original in developing a valid and reliable scale specifically measuring adults' awareness of food label reading - an area less explored in the literature, which mostly emphasizes general nutrition knowledge or label reading frequency.
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    Assessment of malnutrition in hospitalized children: Comparison of stamp, PYMS and strong-kids screening tools
    (Elsevier Science Inc, 2026) Mutlu, Elif; Kokturk, Seda Nur; Soke, Nursena Ersoy; Yardimci, Hulya
    Aim: Early identification of malnutrition risk in hospitalized children is essential for timely nutritional intervention. This study aims diagnostic performance of three pediatric malnutrition screening tools validated in Turkish: STAMP, PYMS, and STRONG-Kids.\n\nMethods: In this cross-sectional study, 148 hospitalized children were included. Nutritional risk was evaluated using STAMP, PYMS, and STRONG-Kids screening tools. Anthropometric measurements were performed, and height-for-age, Body Mass Index (BMI)-for-age, and Middle Upper Arm Circumference (MUAC)-for-age z-scores were calculated. The sensitivity and specificity of each tool were assessed in identifying chronic and acute malnutrition. Receiver operating characteristic (ROC) curve analysis was used to assess the discriminative ability of the screening tools. Results: Chronic malnutrition was identified in 12.8% of patients and acute malnutrition in 15.5%. STAMP and STRONG-Kids showed the highest sensitivity for detecting chronic malnutrition (84.2% and 84.3%), while PYMS had the highest specificity. STRONG-Kids demonstrated the greatest sensitivity for acute malnutrition and low MUAC z-scores (100.0%). ROC analysis showed that PYMS had the highest Area Under the Curve (AUC) for acute malnutrition, whereas STRONG-Kids had the highest AUC for chronic malnutrition, although all tools demonstrated limited discriminative ability for chronic malnutrition.\n\nConclusion: STAMP and STRONG-Kids were more sensitive in detecting malnutrition risk, whereas PYMS showed higher specificity. Tool performance varied according to anthropometric indicators. Implications to practice: In clinical practice, selecting the screening tool according to the targeted malnutrition type and available anthropometric indicators may improve early detection and allow more effective prioritization of nutritional interventions in hospitalized children.\n\n (c) 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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    Ecological and nutritional analysis of artificial intelligence-based sustainable dietary models
    (Academic Press Inc Elsevier Science, 2026) Kokturk, Seda Nur; Yardimci, Hulya
    Growing concerns over environmental sustainability and health have increased the demand for sustainable diets. Advances in artificial intelligence (AI) offer new opportunities for diet planning. Evaluating the nutritional adequacy and environmental impact of AI-generated sustainable diets is essential. This study aimed to compare the nutritional quality and ecological footprints of sustainable diets created by four popular AI tools (Gemini, Copilot, ChatGPT, and Grok). Each AI tool generated a sustainable diet plan for a healthy adult woman. Diets were evaluated for energy, nutrient content, antioxidant capacity, glycemic index, protein quality, fatty acid profiles, Healthy Eating Index-2015 scores, and ecological footprints. All diets showed low ecological footprints but did not meet energy targets (1800 kcal/day). Gemini had the most sustainable composition. Vitamin B12 was consistently below recommended levels in diets from Gemini, Copilot, and ChatGPT. All diets had adequate carbohydrate, protein, fat quality, and overall diet quality. Carbon footprint associated with protein, energy from protein, cholesterol, pyridoxine, folate, and vitamin C. Water footprint was linked to multiple nutrients, and fruits, meat, poultry, and fish; vegetable intake correlated with carbon footprint. AI-assisted diets have potential for sustainability but nutritional completeness concerns remain, especially for vulnerable groups. Further studies comparing AI and dietitian plans are needed to assess long-term effects.
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    Effect of ultra-processed food consumption on premenstrual syndrome across different body mass index categories: a cross-sectional analysis
    (Emerald Group Publishing Ltd, 2026) Kokturk, Seda Nur; Tas Yildirim, Esra; Yardimci, Hulya
    PurposeThis study aimed to examine the association between ultra-processed food (UPF) consumption and premenstrual syndrome (PMS) across different body mass index (BMI) categories in women.Design/methodology/approachA total of 480 women aged 20-49 years participated in the study between May 2024 and May 2025 in 3 cities in T & uuml;rkiye. PMS symptoms were assessed using the Premenstrual Syndrome Scale (PMSS), and UPF intake was evaluated according to the NOVA classification using a food frequency questionnaire. Anthropometric measurements, including height and body weight, were taken by researchers, and BMI was calculated for each participant.FindingsThe mean BMI of the participants was 24.2 +/- 4.9 kg/m2, with an average daily UPF intake of 858.0 +/- 133.3 g. Higher UPF intake was significantly associated with increased reporting of PMS, with 7.0% higher odds among normal-weight women, 19.0% higher odds among overweight women, and 41.0% higher odds among women with obesity. Moreover, as UPF consumption increased from the lowest (Q1) to the highest quartile (Q4), the odds of experiencing PMS symptoms were 2.65 times (OR: 2.65, %95 CI: 1.52-4.61), 2.85 times (OR: 2.85, %95 CI:1.60-4.95), and 3.07 times (OR: 3.07, %95 CI: 1.71-5.49) higher, respectively (p = 0.001).Research limitations/implicationsThese findings underscore a significant association between UPF consumption and PMS symptoms, particularly among women with obesity. Given the high prevalence of PMS and its substantial impact on women's well-being, dietary interventions aimed at reducing UPF intake may represent a promising approach for PMS management and prevention.Originality/valueTo the best of our knowledge, this study is the first to examine the relationship between UPF intake and self-reported PMS presence across different BMI categories.
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    Evaluation of post-traumatic stress disorder and food insecurity in earthquake survivors
    (Springer Heidelberg, 2025) Kokturk, Seda Nur; Esgin, Ozge; Bulbul, Ali Savas; Sahin, Engin
    AimThis study aimed to investigate the psychological difficulties and challenges related to food insecurity following the earthquakes in Kahramanmara & scedil; province on February 6, 2023, particularly examining the relationship between Post-Traumatic Stress Disorder (PTSD) and food insecurity among survivors.Subjects and methodsThe research included 504 adults (71.4% female). The study assessed the subcomponents of food insecurity and measured PTSD levels among participants. It also evaluated the prevalence of Gastrointestinal System (GIS) issues and appetite loss.ResultsIndividuals facing food insecurity exhibited higher median PTSD scores compared to those not experiencing food insecurity. A significant majority of individuals with PTSD (90.2%) also encountered GIS issues, with a notable prevalence of appetite loss. GIS problems were common among those experiencing food insecurity.ConclusionMany disaster victims endure both food insecurity and PTSD, negatively impacting their dietary habits and health. Providing clean, dependable, and nutritious food post-disaster can reduce health risks. Psychological support and therapy for PTSD can aid recovery. More detailed studies on nutritional status are needed for deeper insights.