ArticleNutrients2018
Feasibility of Reviewing Digital Food Images for Dietary Assessment among Nutrition Professionals.
Article in Nutrients, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A comparison of personalized and fixed interval signal-contingent ecological momentary assessment to capture dietary data: a double-blinded crossover feasibility study.European journal of clinical nutrition · 2026Trial
- COVID-19 and Virtual Nutrition: A Pilot Study of Integrating Digital Food Models for Interactive Portion Size Education.Nutrients · 2022Article
- A Novel Approach to Dining Bowl Reconstruction for Image-Based Food Volume Estimation.Sensors (Basel, Switzerland) · 2022Article
- Feasibility and Acceptability of Photographic Food Record, Food Diary and Weighed Food Record in People with Serious Mental Illness.Nutrients · 2021Article
- Integration of an Image-Based Dietary Assessment Paradigm into Dietetic Training Improves Food Portion Estimates by Future Dietitians.Nutrients · 2021Article
- "Everyone can take photos." Feasibility and relative validity of phone photography-based assessment of children's diets - a mixed methods study.Nutrition journal · 2020Article
- Assessing dinner meals offered at home among preschoolers from low-income families with the Remote Food Photography Method.Pediatric obesity · 2019Article
- Food Volume Estimation Based on Deep Learning View Synthesis from a Single Depth Map.Nutrients · 2018Article
- Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Validity of image-assisted and image-based dietary assessment methods relies on the accuracy of portion size estimation based on food images. However, little is known on the ability of nutrition professionals in assessing dietary intake based on digital food images. This study aims to examine the ability of nutrition professionals in reviewing food images with regard to food item identification and portion size estimation. Thirty-eight nutritionists, dietitians, and nutrition researchers participated in this study. Through an online questionnaire, participants' accuracy in identifying food items and estimating portion sizes of two sets of digital food images presenting a meal on a plate (Image PL) and in a bowl (Image BW) were tested. Participants reported higher accuracy in interpreting Image BW compared to Image PL, both in terms of accuracy in food identification (75.3 ± 17.6 vs. 68.9 ± 17.1%) and percentage difference in portion size estimation (44.3 ± 16.6 vs. 47.6 ± 21.2%). Weight of raw vegetables was significantly underestimated (-45.1 ± 22.8% vs. -21.2 ± 37.4%), while drink was significantly overestimated (40.1 ± 45.8% vs. 26.1 ± 32.2) in both images. Less than one-third of the participants estimated portion size within 10% of actual weight for Image PL (23.7%) and Image BW (32.3%). Accuracy of nutrition professionals in reviewing food images could be further improved with training on better perception of portion sizes from images.
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