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Diet, Nutrition and Human Health
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Diet, Nutrition and Human Health

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Food Science and Technology".

Deadline for manuscript submissions: 20 April 2026 | Viewed by 2804

Special Issue Editors

Dr. Te-Chih Wong

E-Mail Website
Guest Editor
Department of Health and Nutrition, Chinese Culture University Taiwan, Taipei, Taiwan
Interests: nutrition; diet quality; clinical nutrition; public health nutrition; renal disease
Dr. Yi-Ping Yu

E-Mail Website
Guest Editor
Department of Nutrition and Health Sciences, Chinese Culture University, Taipei, Taiwan
Interests: nutrition; nutraceuticals; food analysis and inspection; nutritional biochemistry; functional foods

Special Issue Information

Dear Colleagues,

The World Health Organization states that a healthy diet may help protect against malnutrition in all its forms, as well as noncommunicable diseases (NCDs), including diabetes, heart disease, stroke, and cancer. However, the quantities, proportions, variety, and combinations of different foods in diets, as well as food processing and modern methods of functional food production, have led to a shift in human dietary patterns. This Special Issue of "Diet, Nutrition, and Human Health" on "Food Science and Technology" will be dedicated to new perspectives on the intricate relationships among dietary patterns, nutritional intake, nutrient function, and human health outcomes. The topics discussed in this Special Issue will not only seek to bridge the gap between nutrition science and food technology, but will also provide a comprehensive platform for research that can enhance our understanding of how food and nutrient consumption, dietary patterns, functional foods, and nutraceuticals impact human health, as verified by their properties in animal or human studies.

Dr. Te-Chih Wong
Dr. Yi-Ping Yu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • diet
  • nutrition
  • human health
  • dietary patterns
  • food science
  • food technology
  • functional foods
  • nutraceuticals
  • human studies
  • animal research

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Published Papers (3 papers)

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Research

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14 pages, 236 KiB  
Article
The Prognostic Nutritional Index (PNI) Is a Powerful Biomarker for Predicting Clinical Outcome in Gastrointestinal Emergency Patients: A Comprehensive Analysis from Diagnosis to Outcome
by Ramazan Kıyak and Bahadir Caglar
Appl. Sci. 2025, 15(15), 8269; https://doi.org/10.3390/app15158269 - 25 Jul 2025
Viewed by 367
Abstract
Objective: This study aimed to evaluate the relationship between the Prognostic Nutritional Index (PNI) and demographic characteristics, presenting complaints, clinical diagnoses, and patient outcomes in patients admitted to the emergency department for gastrointestinal (GI) emergencies. The predictive value of PNI for the clinical [...] Read more.
Objective: This study aimed to evaluate the relationship between the Prognostic Nutritional Index (PNI) and demographic characteristics, presenting complaints, clinical diagnoses, and patient outcomes in patients admitted to the emergency department for gastrointestinal (GI) emergencies. The predictive value of PNI for the clinical course of patients with GI emergencies was investigated. Method: This retrospective cross-sectional study included 583 patients with a diagnosis of GI emergencies in the emergency department of a tertiary university hospital between January 2021 and December 2024. Data such as age, sex, presenting complaints, final diagnosis, and emergency department outcomes (discharge, ward admission, and transfer to intensive care unit) were collected. The PNI value was calculated using serum albumin (g/dL) and total lymphocyte count (/mm3) with the formula PNI = 10 × albumin + 0.005 × lymphocyte. The PNI was calculated based on serum albumin levels and peripheral lymphocyte counts. Results: The mean age of the study group was 63.4 ± 17.4 years, and 52.1% of the patients were female. The number of patients with a PNI value < 38 was significantly higher in the intensive care unit (p < 0.001). PNI values were considerably lower, especially in patients diagnosed with malignancy, cirrhosis, and GI hemorrhage (X2 = 71.387; p < 0.001). The PNI was an independent predictor of outcomes in patients with GI emergencies. The mean PNI was significantly higher in discharged patients but significantly lower in patients admitted to the intensive care unit (p < 0.002). The cut-off score for PNI was calculated using the median value, and the cut-off score for PNI was <38. Conclusion: PNI is a powerful biomarker for predicting the clinical severity and prognosis of patients with GI emergencies. Since it can be easily calculated from routine biochemical tests, it can be used as a practical and effective risk stratification tool. The evaluation of PNI, especially for the early detection of critically ill patients at high risk of malnutrition, may contribute to the reduction of morbidity and mortality through the timely initiation of appropriate supportive therapies. Full article
(This article belongs to the Special Issue Diet, Nutrition and Human Health)
17 pages, 1125 KiB  
Article
Factors of Weight Loss for Telemedically Supported Metabolic Syndrome Patients in a Controlled Trial
by Brigitta Szálka, István Vassányi, Éva Máthéné Köteles, Lili Adrienn Szabó, Szilvia Lada, Tímea Bolgár, Andrea Korom, Judit Ábrahám, Vilmos Bilicki, Mária Barnai, Attila Nemes, Csaba Lengyel and István Kósa
Appl. Sci. 2024, 14(22), 10179; https://doi.org/10.3390/app142210179 - 6 Nov 2024
Viewed by 1464
Abstract
Metabolic syndrome (MetS) is a complex of interrelated risk factors, associated with several serious chronic diseases like diabetes. The goal of this study was to find dietary factors of successful weight loss for MetS outpatients. We performed a 90-day dietary intervention in a [...] Read more.
Metabolic syndrome (MetS) is a complex of interrelated risk factors, associated with several serious chronic diseases like diabetes. The goal of this study was to find dietary factors of successful weight loss for MetS outpatients. We performed a 90-day dietary intervention in a telemedically supported, pre- and post-test, controlled trial in Hungary involving 132 MetS patients; 67 were in the intervention, and 65 were in the control group. Patients in the intervention group used wireless smart devices, a dietary logger, and a lifestyle app. During the trial, we recorded the patients’ weight loss and diet composition. For analysis, t-tests were used, and the temporal trends of diet composition in the intervention group were analyzed between two sub-groups according to weight loss success. Correlation and regression models were used to find predictors of success. The intervention group achieved more weight loss, and the success in this group was linked with more consumption of raw fruits/vegetables, poultry and potato dishes, while age had a negative effect. We conclude that telemedically supported dietary coaching is an efficient alternative for interventions directed at weight loss. Future trials should investigate the therapeutic application of diets rich in raw fruits, especially apples, and vegetables, as well as poultry dishes. Full article
(This article belongs to the Special Issue Diet, Nutrition and Human Health)
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Review

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35 pages, 3289 KiB  
Review
Applications of Machine Learning Algorithms in Geriatrics
by Adrian Stancu, Cosmina-Mihaela Rosca and Emilian Marian Iovanovici
Appl. Sci. 2025, 15(15), 8699; https://doi.org/10.3390/app15158699 - 6 Aug 2025
Viewed by 359
Abstract
The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, [...] Read more.
The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. This paper presents a systematic review of the scientific literature published between 1 January 2020 and 31 May 2025. The paper is based on the applicability of ML techniques in the field of geriatrics. The study is conducted using the Web of Science database for a detailed discussion. The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. The performance metrics reported in the analyzed papers include the accuracy, sensitivity, F1-score, and Area under the Receiver Operating Characteristic Curve. Nine search categories are investigated through four databases: WOS, PubMed, Scopus, and IEEE. A comparative analysis shows that the field of geriatrics, through an ML approach in the context of elderly nutrition, is insufficiently explored, as evidenced by the 61 articles analyzed from the four databases. The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. The paper highlights the potential of ML models in transforming geriatrics within the context of personalized predictive care and outlines a series of future research directions, recommending the development of standardized databases, the integration of algorithmic explanations, the promotion of interdisciplinary collaborations, and the implementation of ethical norms of artificial intelligence in geriatric medical practice. Full article
(This article belongs to the Special Issue Diet, Nutrition and Human Health)
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