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Nutrients
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New Advances in Dietary Assessment
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New Advances in Dietary Assessment

A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition Methodology & Assessment".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 6967

Special Issue Editor

Dr. Claire Timon

E-Mail Website
Guest Editor
School of Population Health, RCSI University of Medicine and Health Sciences, Dublin, Ireland
Interests: nutrition; dietary assessment; digital health; lifestyle behaviour change; public health

Special Issue Information

Dear Colleagues,

Accurate measurements of dietary intake are fundamental to health and nutrition research; yet diet is inherently complex to measure due to its variability over time and across life stages. Recent technological advances have revolutionised dietary assessment, utilising mobile phones, sensors, wearable cameras, web-based platforms, biomarkers of nutrient intake, and more recently, artificial intelligence. These innovative methods have become popular alternatives to traditional pen-and-paper assessments, facilitating data collection across diverse geographic locations and often being preferred by participants. Technology-enhanced dietary assessments have been shown to reduce costs and provide more detailed and dynamic insights into dietary behaviours. However, using new technologies in dietary assessment also presents challenges, such as ensuring data accuracy and, in some cases, overcoming user adoption barriers.

This Special Issue invites contributions that explore innovative approaches and technologies in dietary assessment. We seek original research and review articles that demonstrate the application of these advancements in various populations and settings. Topics of interest include, but are not limited to, the following:

  • Development and validation of new dietary assessment tools;
  • Application of digital health technologies in dietary assessment;
  • Use of big data and artificial intelligence in nutritional epidemiology;
  • Integration of dietary assessment with biomarkers and genetic data;
  • Cross-cultural adaptations of dietary assessment methods;
  • Innovative approaches for analysing dietary intake data.

By showcasing cutting-edge research, this Special Issue aims to provide a comprehensive overview of the state of the art in dietary assessment. We hope to stimulate further innovation and collaboration in the field, ultimately leading to improved dietary assessment approaches. We encourage researchers and practitioners from diverse disciplines to contribute to this Special Issue by sharing their findings and perspectives on innovative approaches to collecting and analysing dietary intake data. These advances can provide greater insight into dietary behaviours across populations, enhancing our understanding of diet–health relationships and supporting public health efforts worldwide.

Dr. Claire Timon
Guest Editor

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. Nutrients 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 2900 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

  • dietary assessment
  • nutritional epidemiology
  • digital health
  • big data and AI
  • dietary patterns
  • biomarkers

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

15 pages, 444 KiB  
Article
A Study on Dining-Out Habits Among Beijing Residents: A Case of Fast Food
by Zhishan Liu, Wenqiang Chen, Aoran Cui, Kaibiao Gu and Shijun Lu
Nutrients 2025, 17(4), 738; https://doi.org/10.3390/nu17040738 - 19 Feb 2025
Viewed by 841
Abstract
Background: With the continuous elevation of living standards, dining-out behavior has become increasingly prevalent among urban residents. The acceleration of lifestyle rhythms has prompted fast food to emerge as a frequently considered dietary option for urban residents when dining out. This study [...] Read more.
Background: With the continuous elevation of living standards, dining-out behavior has become increasingly prevalent among urban residents. The acceleration of lifestyle rhythms has prompted fast food to emerge as a frequently considered dietary option for urban residents when dining out. This study aims to investigate the current status and characteristics of dining-out habits for fast-food consumption among urban residents in Beijing. Methods: Urban residents in Beijing were selected using a stratified sampling method to survey restaurants. A database of fast-food items was created, and data were collected through a combination of field observations and qualitative interviews. Nutrient intake from fast food was systematically analyzed. Results: Residents consuming fast food while dining out exhibited high per-meal energy intake (737.5 kcal) and protein (44.8 g) consumption; however, the intakes of vitamin A (147.6 μg RAE), vitamin C (22 mg), vitamin E (3.2 mg), and calcium (89.5 mg) were inadequate. Western fast-food meals had higher protein (57.2 g) and sodium (251.5 mg) content compared to Chinese fast food. Conclusions: This study provides essential data to guide urban residents toward rational dining choices, offering key insights for the fast-food industry to develop balanced meal options. Full article
(This article belongs to the Special Issue New Advances in Dietary Assessment)
15 pages, 890 KiB  
Article
An Evaluation of ChatGPT for Nutrient Content Estimation from Meal Photographs
by Cathal O’Hara, Gráinne Kent, Angela C. Flynn, Eileen R. Gibney and Claire M. Timon
Nutrients 2025, 17(4), 607; https://doi.org/10.3390/nu17040607 - 7 Feb 2025
Viewed by 2774
Abstract
Background/Objectives: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This study aimed to evaluate the accuracy of ChatGPT-4 in estimating nutritional content of commonly [...] Read more.
Background/Objectives: Advances in artificial intelligence now allow combined use of large language and vision models; however, there has been limited evaluation of their potential in dietary assessment. This study aimed to evaluate the accuracy of ChatGPT-4 in estimating nutritional content of commonly consumed meals using meal photographs derived from national dietary survey data. Methods: Meal photographs (n = 114) were uploaded to ChatGPT and it was asked to identify the foods in each meal, estimate their weight, and estimate the nutrient content of the meals for 16 nutrients for comparison with the known values using precision, paired t-tests, Wilcoxon signed rank test, percentage difference, and Spearman correlation (rs). Seven dietitians also estimated energy, protein, and carbohydrate content of thirty-eight meal photographs for comparison with ChatGPT using intraclass correlation (ICC). Results: Comparing ChatGPT and actual meals, ChatGPT showed good precision (93.0%) for correctly identifying the foods in the photographs. There was good agreement for meal weight (p = 0.221) for small meals, but poor agreement for medium (p < 0.001) and large (p < 0.001) meals. There was poor agreement for 10 of the 16 nutrients (p < 0.05). Percentage difference from actual values was >10% for 13 nutrients, with ChatGPT underestimating 11 nutrients. Correlations were adequate or good for all nutrients with rs ranging from 0.29 to 0.83. When comparing ChatGPT and dietitians, the ICC ranged from 0.31 to 0.67 across nutrients. Conclusions: ChatGPT performed well for identifying foods, estimating weights of small portion sizes, and ranking meals according to nutrient content, but performed poorly for estimating weights of medium and large portion sizes and providing accurate estimates of nutrient content. Full article
(This article belongs to the Special Issue New Advances in Dietary Assessment)
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12 pages, 305 KiB  
Article
Analysis of Toxic Element Levels and Health Risks in Different Soybean Species (Glycine max, Vigna radiata, Vigna angularis, Vigna mungo)
by Juan R. Jáudenes-Marrero, Greta Giannantonio, Soraya Paz-Montelongo, Arturo Hardisson, Javier Darias-Rosales, Dailos González-Weller, Ángel J. Gutiérrez, Carmen Rubio and Samuel Alejandro-Vega
Nutrients 2024, 16(24), 4290; https://doi.org/10.3390/nu16244290 - 12 Dec 2024
Viewed by 1170
Abstract
Background: Soybeans are a widely consumed legume, essential in Western diets and especially prominent in vegan and vegetarian nutrition. However, environmental contamination from anthropogenic sources, such as industrial emissions, wastewater, and pesticide use, has led to the accumulation of non-essential and toxic elements [...] Read more.
Background: Soybeans are a widely consumed legume, essential in Western diets and especially prominent in vegan and vegetarian nutrition. However, environmental contamination from anthropogenic sources, such as industrial emissions, wastewater, and pesticide use, has led to the accumulation of non-essential and toxic elements in legumes, potentially impacting human health. Method: This study quantified the levels of 11 potential toxic elements (Al, B, Ba, Cd, Co, Cr, Li, Ni, Pb, Sr, V) in 90 samples of four soybean species (Glycine max, Vigna radiata, Vigna angularis, Vigna mungo) using inductively coupled plasma optical emission spectrometry (ICP-OES). Results: Results showed that boron had the highest mean content (9.52 mg/kg ww), followed by aluminum (6.73 mg/kg ww). Among the toxic metals, cadmium was most concentrated in green soybeans (0.03 mg/kg ww), and black soybeans had the highest level of lead (0.07 mg/kg ww). Based on an average soybean consumption of 50 g/day, no immediate health risk was detected. However, lithium and nickel were present in substantial amounts, with lithium contributing 31.43–48.57% and nickel 6.81–39.56% of their respective provisional daily intake limits, especially from red soybeans (V. angularis). Conclusions: This study highlights the importance of monitoring toxic elements in soybeans and calls for stricter environmental management practices to minimize contamination, ensuring the safety of soy products as their global consumption rises. Full article
(This article belongs to the Special Issue New Advances in Dietary Assessment)
13 pages, 606 KiB  
Article
Acceptance, Needs, and Demands for Nutritional mHealth Support in Patients with Cardiovascular Disease
by Darya Mohajeri, Lisa Maria Jahre, Alexander Bäuerle, Theresa Schieffers, Daniel Messiha, Christos Rammos, Martin Teufel, Tienush Rassaf and Julia Lortz
Nutrients 2024, 16(23), 4155; https://doi.org/10.3390/nu16234155 - 30 Nov 2024
Viewed by 1618
Abstract
Background: Cardiovascular diseases (CVDs) are the leading causes of death globally. Managing risk factors and preventing atherosclerosis and its progress, especially with lifestyle changes, are highly important. Smartphone-based mobile health (mHealth) strategies allow easily accessible assistance for healthy nutrition. This study aimed to [...] Read more.
Background: Cardiovascular diseases (CVDs) are the leading causes of death globally. Managing risk factors and preventing atherosclerosis and its progress, especially with lifestyle changes, are highly important. Smartphone-based mobile health (mHealth) strategies allow easily accessible assistance for healthy nutrition. This study aimed to assess the acceptance and outline the needs and demands for a nutritional mHealth tool by analyzing the desired characteristics. Methods: A cross-sectional study was conducted between August 2022 and September 2023 targeting 398 individuals with atherosclerosis. Acceptance, needs, and demands regarding mHealth, sociodemographic, medical, psychometric, and electronic health (eHealth) data were assessed. Multiple hierarchical regression analyses were conducted to determine the predictors of acceptance. Results: High acceptance for nutritional mHealth was reported by 88.4% (n = 274). Significant predictors of acceptance were age (β = −0.01, p = 0.002), diabetes (β = 0.20, p = 0.041), depressive symptoms (β = −0.02, p = 0.017), digital confidence (β = 0.17, p = 0.001), Internet anxiety (β = −0.18, p = 0.004), and the Unified Theory of Acceptance and Use of Technology (UTAUT) predictors effort expectancy (β = 0.23, p < 0.001) and social influence (β = 0.53, p < 0.001). Preferences included handheld devices, permanent use (86.5%), and weekly (44.5%) new content of 10 to 30 min (79%). Conclusions: These results summarize the patients’ preferences for individualized mHealth tools to ensure their effectiveness. Especially regarding the secondary prevention of CVDs, mHealth can be a helpful resource. The high acceptance rate and specific preferences outlined in this study form a strong basis for the development of mHealth tools with a focus on nutritional support in patients with CVDs. Full article
(This article belongs to the Special Issue New Advances in Dietary Assessment)
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