Comparison of Known Food Weights with Image-Based Portion-Size Automated Estimation and Adolescents' Self-Reported Portion Size
Open accessAbstract
Background: Diet is a critical element of diabetes self-management. An emerging area of research is the use of images for dietary records using mobile telephones with embedded cameras. These tools are being designed to reduce user burden and to improve accuracy of portion-size estimation through automation. The objectives of this study were to (1) assess the error of automatically determined portion weights compared to known portion weights of foods and (2) to compare the error between automation and human. Methods: Adolescents ( n = 15) captured images of their eating occasions over a 24 h period. All foods and beverages served were weighed. Adolescents self-reported portion sizes for one meal. Image analysis was used to estimate portion weights. Data analysis compared known weights, automated weights, and self-reported portions. Results: For the 19 foods, the mean ratio of automated weight estimate to known weight ranged from 0.89 to 4.61, and 9 foods were within 0.80 to 1.20. The largest error was for lettuce and the most accurate was strawberry jam. The children were fairly accurate with portion estimates for two foods (sausage links, toast) using one type of estimation aid and two foods (sausage links, scrambled eggs) using another aid. The automated method was fairly accurate for two foods (sausage links, jam); however, the 95% confidence intervals for the automated estimates were consistently narrower than human estimates. Conclusions: The ability of humans to estimate portion sizes of foods remains a problem and a perceived burden. Errors in automated portion-size estimation can be systematically addressed while minimizing the burden on people. Future applications that take over the burden of these processes may translate to better diabetes self-management.
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Traditional dietary self-monitoring methods suffer from underreporting and recall issues.
“These methods can be burdensome to people [6,7,15-17] and suffer from underreporting and recall issues [15-19].”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [19]
Portion size estimation is difficult even when measurement aids are present in the picture.
“Portion size estimation is difficult even when measurement aids are present in the picture [18,19,38].”
From Factors related to sustained use of a free mobile app for dietary self-monitoring with photography and peer feedback: retrospective cohort study (2014) · cites this paper as [19]
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- Authors
- Lee, C. D., Chae, J., Schap, T. E., Kerr, D. A., Delp, E. J., Ebert, D. S., & Boushey, C. J.
- Affiliations
- Purdue University West Lafayette (US)
- Curtin University (AU)
- Corresponding author
- Boushey, Carol J.
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2012-03
- Volume
- 6
- Issue
- 2
- Pages
- 428-434
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC3380789
- OpenAlex
- W2147707785
- Cited by
- 58
- References
- 33
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 1 · 2022: 4 · 2021: 3 · 2020: 4 · 2019: 4 · 2018: 4 · 2017: 7 · 2016: 5 · 2015: 6 · 2014: 8 · 2013: 7
- FWCI
- 11.93
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eSpace (Curtin University) (submittedVersion)
- Funders
- National Cancer Institute (U01CA130784)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK073711)
- National Center for Research Resources (TL1RR025759)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Nursing › Nutrition and Dietetics › Nutrition, Health and Food Behavior
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- portion size estimation, adolescents, dietary records, smartphone camera, diabetes self-management, estimation accuracy
- MeSH terms
- Adolescent, Adolescent Behavior, Automation, Beverages, Energy Intake, Child, Eating, Feeding Behavior, Female, Food, Humans, Indiana, Male, Photography, Size Perception, Weights and Measures, Reproducibility of Results, Nutrition Policy, Cell Phone, Self Report
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