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New technology in dietary assessment: a review of digital methods in improving food record accuracy

  • Phyllis J. Stumbo (a1)
Abstract

Methods for conducting dietary assessment in the United States date back to the early twentieth century. Methods of assessment encompassed dietary records, written and spoken dietary recalls, FFQ using pencil and paper and more recently computer and internet applications. Emerging innovations involve camera and mobile telephone technology to capture food and meal images. This paper describes six projects sponsored by the United States National Institutes of Health that use digital methods to improve food records and two mobile phone applications using crowdsourcing. The techniques under development show promise for improving accuracy of food records.

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Corresponding author
Corresponding author: Dr Phyllis J. Stumbo, fax +1 319 248 0222, email Phyllis-stumbo@uiowa.edu
References
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1. Medlin, C & Skinner, JD (1988) 50 year review of individual methods. J Am Dietetic Assoc 88, 1250.
2. Leichsenring, JM & Donelson, WE (1951). Food composition table for short method of dietary analysis (2nd rev). J Am Diet Assoc 27, 386389.
3. Basiotis, PP, Welsh, SO, Cronin, FJ et al. (1988) Number of days of food intake records required to estimate individual and group nutrient intakes with defined confidence. J Nutr 117, 16381641.
4. Dodd, K, Guenther, PM, Freedman, LW et al. (2006) Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc 106, 16401650.
5. Tooze, JA, Kipnis, V, Buckman, DW et al. (2010) A mixed effects model approach for estimating the distribution of usual intake of nutrients: the NCI method. Stat Med 29, 28572868.
6. Hankin, JH, Stallones, RA & Messinger, HB (1968) A short dietary method for epidemiologic studies. III. Development of questionnaire. Am J Epidemiol 87, 285298.
7. Hankin, JH, Messinger, HB & Stallones, RA (1970) A short dietary method for epidemiologic studies. IV. Evaluation of questionnaire. Am J Epidemiol 91, 562567.
8. Block, G, Hartman, AM, Dresser, CM et al. (1986) A data-based approach to diet questionnaire design and testing. Am J Epidemiol 124, 453469.
9. Willet, W (1998) Chapter 5, Food Frequency Methods. In: Nutritional Epidemiology, 2nd ed., pp. 74100. New York: Oxford University Press.
10. Subar, AF, Thompson, FE, Kipnis, V et al. (2001) Comparative validation of the Block, Willett, and National Cancer Institute Food Frequency Questionnaires, the eating at America's table study. Am J Epidemiol 154, 10891099.
11. Subar, AF, Kipnis, V, Troiano, RP et al. (2003) Using intake biomarkers to evaluate the extent of dietary misreporting in a large sample of adults: the OPEN study. Am J Epidemiol 158, 113.
12. Nelson, M, Atkinson, M & Darbyshire, S (1966) Food photography II: use of food photographs for estimating portion size and the nutrient content of meals. Br J Nutr 76, 3149.
13. Foster, E, Matthews, JNS, Lloyd, J et al. (2008) Children's estimates of food portion size: the development and evaluation of three portion size assessment tools for use with children. Br J Nutr 99, 175184.
14. US National Health and Nutrition Examination Study (2002) Food Model Booklet. http://www.cdc.gov/nchs/nhanes/measuring_guides_dri/2002/fmb.htm (accessed 3 September 2012).
15. University of Pittsburgh, Office of Public Affairs, News for November 6, 2011. http://www.news.pitt.edu/news/pitt-researchers-develop-ebutton-easier-way-monitor-food-intake-exercise-and-lifestyl/ (accessed 6 September 2012).
16. Zhang, Z (2010) Food volume estimation from a single image using virtual reality technology. MS Thesis, Swanson School of Engineering, University of Pittsburgh.
17. Khanna, N, Boushey, CJ, Kerr, D, et al. (2010) An overview of the technology assisted dietary assessment project at Purdue University. In: Proceedings of the IEEE International Symposium on Multimedia, pp. 290295. PMID: 22020443; PMCID: PMC3183748, available at http://www.ncbi.nlm.nih.gov/pmc/articles/PC3183748/
18. Zhu, F, Bosch, M, Khanna, N et al. . (2010) Multilevel segmentation for food classification in dietary assessment. Proc Int Symp Image Signal Process Anal 2011, 337342. PMID: PMC 22127051.
19. Zhu, F, Bosch, M, Schap, T et al. (2011) Segmentation assisted food classification for dietary assessment. Proc SPIE 2011, 787378730B. PMID: PMC 22127051.
20. Zhu, F, Bosch, M, Woo, I et al. (2010) The use of mobile devices in aiding dietary assessment and evaluation. IEEE J Sel Top Signal Process 4, 756766. PMID: PMC 20862266.
21. Zhu, F, Bosch, M, Boushey, CJ et al. . (2010) An image analysis system for dietary assessment and evaluation. Proc Int Conf Image Proc 2010;18531856. PMID: PMC 22025261.
22. Puri, M, Zhu, Zhiwei, Yu, Qian et al. (2009) Recognition and volume estimation of food intake using a mobile device. Applications in Computer Vision, 2009. Workshop on Digital Object Identifier, available at zhisdizhu.com/papers/FIVR_mobileDevice_2009.pdf
23. The NCI Automated Self-Administered 24-Hour Recall (ASA24), https://asa24.westat.com/ (accessed 9 July 2012).
24. Janet Cade – Centre for Epidemiology and Biostatistics, School of Food Science and Nutrition, University of Leeds, Leeds, Great Britain.
25. USDA ARS Food Surveys Research Group, Food and Nutrient Database for Dietary Studies. http://www.ars.usda.gov/Services/docs.htm?docid=12089. (accessed 6 September 2012).
26. Lee, CD, Chae, J, Schap, TE et al. (2012) Comparison of known food weights with image-based portion-size automated estimation and adolescents' self-reported portion size. J Diabetes Sci Technol 6, 17. PMID: PMC 22538157.
27. Noronha, J, Hysen, E, Zhang, H et al. (2011) PlateMate: Crowdsourcing nutrition analysis from food photographs. In: UIST Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 112, doi:10.1145/2047196.2047198, available at https:wiki.engr.illinois.edu/download/attachments/181174324/noronha-platemate-uist11-small.pdf.
28. Dawes, D, Faust, D & Meehl, PE (1989). Clinical vs actuarial judgment. Science 243, 16681674.
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Proceedings of the Nutrition Society
  • ISSN: 0029-6651
  • EISSN: 1475-2719
  • URL: /core/journals/proceedings-of-the-nutrition-society
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