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Traditional methods v. new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015

  • B. Amoutzopoulos (a1), T. Steer (a1), C. Roberts (a2), J. E. Cade (a3), C. J. Boushey (a4), C. E. Collins (a5), E. Trolle (a6), E. J. de Boer (a7), N. Ziauddeen (a1), C. van Rossum (a7), E. Buurma (a7), D. Coyle (a5) and P. Page (a1)...
Abstract

The aim of the present paper is to summarise current and future applications of dietary assessment technologies in nutrition surveys in developed countries. It includes the discussion of key points and highlights of subsequent developments from a panel discussion to address strengths and weaknesses of traditional dietary assessment methods (food records, FFQ, 24 h recalls, diet history with interviewer-assisted data collection) v. new technology-based dietary assessment methods (web-based and mobile device applications). The panel discussion ‘Traditional methods v. new technologies: dilemmas for dietary assessment in population surveys’, was held at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, September 2015. Despite respondent and researcher burden, traditional methods have been most commonly used in nutrition surveys. However, dietary assessment technologies offer potential advantages including faster data processing and better data quality. This is a fast-moving field and there is evidence of increasing demand for the use of new technologies amongst the general public and researchers. There is a need for research and investment to support efforts being made to facilitate the inclusion of new technologies for rapid, accurate and representative data.

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      Traditional methods v. new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015
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      Traditional methods v. new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015
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      Traditional methods v. new technologies – dilemmas for dietary assessment in large-scale nutrition surveys and studies: a report following an international panel discussion at the 9th International Conference on Diet and Activity Methods (ICDAM9), Brisbane, 3 September 2015
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Corresponding author
*Corresponding author: B. Amoutzopoulos, email birdem.amoutzopoulos@mrc-ewl.cam.ac.uk
References
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1.Long, JD, Boswell, C, Rogers, TJ, et al. (2013) Effectiveness of cell phones and mypyramidtracker.gov to estimate fruit and vegetable intake. Appl Nurs Res 26, 1723.
2.European Food Safety Authority (2014) Guidance on the EU menu methodology. EFSA J 12, 3944.
3.Ahluwalia, N, Dwyer, J, Terry, A, et al. (2016) Update on NHANES dietary data: focus on collection, release, analytical considerations, and uses to inform public policy. Adv Nutr 7, 121134.
4.Mensink, GB, Haftenberger, M & Thamm, M (2001) Validity of DISHES 98, a computerised dietary history interview: energy and macronutrient intake. Eur J Clin Nutr 55, 409417.
5.Slimani, N, Casagrande, C, Nicolas, G, et al. (2011) The standardized computerized 24-h dietary recall method EPIC-Soft adapted for pan-European dietary monitoring. Eur J Clin Nutr 65, Suppl. 1, S5S15.
6.Crispim, SP, Nicolas, G, Casagrande, C, et al. (2014) Quality assurance of the international computerised 24 h dietary recall method (EPIC-Soft). Br J Nutr 111, 506515.
7.Biltoft-Jensen, A, Hjorth, MF, Trolle, E, et al. (2013) Comparison of estimated energy intake using Web-based Dietary Assessment Software with accelerometer-determined energy expenditure in children. Food Nutr Res 57, 21434.
8.Biltoft-Jensen, A, Damsgaard, CT, Andersen, EW, et al. (2016) Validation of reported whole-grain intake from a web-based dietary record against plasma alkylresorcinol concentrations in 8- to 11-year-olds participating in a randomized controlled trial. J Nutr 146, 377383.
9.Subar, AF, Kirkpatrick, SI, Mittl, B, et al. (2012) The Automated Self-Administered 24-hour Dietary Recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute. J Acad Nutr Diet 112, 11341137.
10.Forster, H, Fallaize, R, Gallagher, C, et al. (2014) Online dietary intake estimation: the Food4Me food frequency questionnaire. J Med Internet Res 16, e150.
11.Collins, CE, Boggess, MM, Watson, JF, et al. (2014) Reproducibility and comparative validity of a food frequency questionnaire for Australian adults. Clin Nutr 33, 906914.
12.Liu, B, Young, H, Crowe, FL, et al. (2011) Development and evaluation of the Oxford WebQ, a low-cost, web-based method for assessment of previous 24 h dietary intakes in large-scale prospective studies. Public Health Nutr 14, 19982005.
13.Carter, MC, Albar, SA, Morris, MA, et al. (2015) Development of a UK online 24-h dietary assessment tool: myfood24. Nutrients 7, 40164032.
14.Simpson, E, Bradley, J, Poliakov, I, et al. (2017) Iterative development of an online dietary recall tool: INTAKE24. Nutrients 9, 118.
15.Boushey, CJ, Harray, AJ, Kerr, DA, et al. (2015) How willing are adolescents to record their dietary intake? The mobile food record. JMIR Mhealth Uhealth 3, e47.
16.Casperson, SL, Sieling, J, Moon, J, et al. (2015) A mobile phone food record app to digitally capture dietary intake for adolescents in a free-living environment: usability study. JMIR Mhealth Uhealth 3, e30.
17.Rollo, ME, Ash, S, Lyons-Wall, P, et al. (2015) Evaluation of a mobile phone image-based dietary assessment method in adults with type 2 diabetes. Nutrients 7, 48974910.
18.Forster, H, Walsh, MC, Gibney, MJ, et al. (2016) Personalised nutrition: the role of new dietary assessment methods. Proc Nutr Soc 75, 96105.
19.Conrad, J & Nothlings, U (2017) Innovative approaches to estimate individual usual dietary intake in large-scale epidemiological studies. Proc Nutr Soc 76, 213219.
20.Bates, B, Cox, L, Nicholson, S, et al. (2016) National Diet and Nutrition Survey: results from years 5 and 6 (combined) of the Rolling Programme (2012/2013–2013/2014). https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/551352/NDNS_Y5_6_UK_Main_Text.pdf (accessed November 2017).
21.Pedersen, AN, Christensen, T, Matthiessen, J, et al. (2015) Dietary habits in Denmark 2011–2013. http://orbit.dtu.dk/files/110628064/Rapport_Danskernes_Kostvaner_2011_2013.pdf (accessed July 2017).
22.van Rossum, CTM, Buurma-Rethans, EJM, Venneman, FBV, et al. (2016) The diet of the Dutch: results of the first two years of the Dutch National Food Consumption Survey 2012–2016. http://www.rivm.nl/en/Documents_and_publications/Scientific/Reports/2016/november/The_diet_of_the_Dutch_Results_of_the_first_two_years_of_the_Dutch_National_Food_Consumption_Survey_2012_2016 (accessed July 2017).
23.Castetbon, K, Vernay, M, Malon, A, et al. (2009) Dietary intake, physical activity and nutritional status in adults: the French Nutrition and Health Survey (ENNS, 2006–2007). Br J Nutr 102, 733743.
24.Thompson, FE, Subar, AF, Loria, CM, et al. (2010) Need for technological innovation in dietary assessment. J Am Diet Assoc 110, 4851.
25.Amcoff, E, Edberg, A, Barbieri, HE, et al. (2012) Riksmaten – Adults 2010–11, Livsmedels- och näringsintag bland vuxna i Sverige (Food and nutrient intake among adults in Sweden). https://www.webcitation.org/6btKQVMMi (accessed October 2017).
26.Warensjö Lemming, E & Lindroos, AK (2017) Web-based dietary assessment – experiences from the national dietary surveys in Sweden. Max Rubner Conference 2017, Nutrition Monitoring – Challenges and Developments, 9–11 October 2017, Karlsruhe, Germany, Abstract 12. https://www.mri.bund.de/fileadmin/MRI/Events/MRC/MRI_MRC2017_Abstracts_final_web-c.pdf (accessed March 2018).
27.Macdiarmid, J & Blundell, J (1998) Assessing dietary intake: who, what and why of under-reporting. Nutr Res Rev 11, 231253.
28.Subar, AF, Freedman, LS, Tooze, JA, et al. (2015) Addressing current criticism regarding the value of self-report dietary data. J Nutr 145, 26392645.
29.Keeble, C, Baxter, PD, Barber, S, et al. (2016) Participation rates in epidemiology studies and surveys: a review 2007–2015. Internet J Epidemiol 14, 114.
30.Lutien, A, De Leeuw, E & Hox, J (2017) Results of the (new) International Questionnaire on Non-response: response of the LFS and other surveys. International Workshop on Household Survey Nonresponse, Utrecht, the Netherlands, 30 August–1 September 2017. http://www.nonresponse.org/c/554/Keynote_and_special_session_/?preid=556 (accessed March 2018).
31.Carrillo, S & Dubuisson, C (2016) Matching food consumption and food composition data: the challenge of the food linkage. http://www.eurofir.org/foodforum2016/wp-content/uploads/sites/3/2016/05/FranceRichfields_Bruxelles_08_04_2016_V3.pdf (accessed October 2017).
32.Toxopeus, I, Ocké, M & Westenbrink, S (2016) Dutch tool(s) for food matching. http://www.eurofir.org/foodforum2016/wp-content/uploads/sites/3/2016/05/Dutch_FoodMatchingTool_20160408_v2.pdf (accessed October 2017).
33.Carter, MC, Hancock, N, Albar, SA, et al. (2016) Development of a new branded UK food composition database for an online dietary assessment tool. Nutrients 8, 480.
34.US Department of Agriculture (2017) USDA branded food products database documentation. https://ndb.nal.usda.gov/ndb/docs/BFPDB_Doc.pdf (accessed December 2017).
35.Australian Bureau of Statistics (2013) Australian Health Survey: users' guide, 2011–13. http://www.abs.gov.au/ausstats/abs@.nsf/mf/4363.0.55.001 (accessed July 2017).
36.Food Standards Australia New Zealand (2015) Australian Food, Supplement and Nutrient Database (AUSNUT). http://www.foodstandards.gov.au/science/monitoringnutrients/ausnut/foodnutrient/Pages/default.aspx (accessed December 2017).
37.Australian Bureau of Statistics (2014) Australian Health Survey: Nutrition First Results – Foods and Nutrients, 2011–12. http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/4364.0.55.007main+features12011-12 (accessed July 2017).
38.Watson, JF, Collins, CE, Sibbritt, DW, et al. (2009) Reproducibility and comparative validity of a food frequency questionnaire for Australian children and adolescents. Int J Behav Nutr Phys Act 6, 62.
39.The University of Newcastle, Newcastle Innovation™ (2013) Healthy Eating Quiz. http://healthyeatingquiz.com.au/ (accessed July 2017).
40.Medin, AC, Hansen, BH, Astrup, H, et al. (2017) Validation of energy intake from a web-based food recall for children and adolescents. PLOS ONE 12, e0178921.
41.Trolle, E, Gondolf, UH, Ege, M, et al. (2013) Dietary survey of infants and young children 2006–2007. http://www.food.dtu.dk/english/-/media/Institutter/Foedevareinstituttet/Publikationer/Pub-2013/Rapport-Danskernes-kostvaner-spaed-og-smaaboern-rev-12-12-13-1-.ashx?la=da (accessed July 2017).
42.Lutomski, JE, van den Broeck, J, Harrington, J, et al. (2011) Sociodemographic, lifestyle, mental health and dietary factors associated with direction of misreporting of energy intake. Public Health Nutr 14, 532541.
43.National Institute for Public Health and the Environment (2016) DNFCS 2012–2016, 1–79 years. http://www.rivm.nl/en/Topics/D/Dutch_National_Food_Consumption_Survey/Overview_surveys/DNFCS_2012_2016#Method (accessed July 2017).
44.National Institute for Public Health and the Environment (2016) Dutch Food Composition Database. http://www.rivm.nl/en/Topics/D/Dutch_Food_Composition_Database (accessed November 2017).
45.National Institute for Public Health and the Environment (2011) Dutch Dietary Supplement Database. http://www.rivm.nl/en/Topics/D/Dutch_Food_Composition_Database/Organisation/Dutch_Dietary_Supplement_Database (accessed November 2017).
46.Bates, B, Lennox, A, Prentice, A, et al. (2014) National Diet and Nutrition Survey: results from Years 1, 2, 3 and 4 (combined) of the Rolling Programme (2008/2009–2011/2012). https://www.gov.uk/government/statistics/national-diet-and-nutrition-survey-results-from-years-1-to-4-combined-of-the-rolling-programme-for-2008-and-2009-to-2011-and-2012 (accessed July 2017).
47.Fitt, E, Cole, D, Ziauddeen, N, et al. (2015) DINO (Diet In Nutrients Out) – an integrated dietary assessment system. Public Health Nutr 18, 234241.
48.Burley, VJ, Timmins, K, Cade, J, et al. (2014) Making the best use of new technologies in the National Diet and Nutrition Survey: a review. http://eprints.lincoln.ac.uk/23781/1/NDNS%20New%20Technologies%20Review.pdf (accessed July 2017).
49.Research Councils, UK (2016) A UK on-line 24 h dietary recall tool for population studies: development, validation and practical application. http://gtr.rcuk.ac.uk/projects?ref=G1100235 (accessed November 2017).
50.Albar, SA, Alwan, NA, Evans, CE, et al. (2016) Agreement between an online dietary assessment tool (myfood24) and an interviewer-administered 24-h dietary recall in British adolescents aged 11–18 years. Br J Nutr 115, 16781686.
51.Rowland, M, Poliakov, I, Christie, S, et al. (2016) Field testing of the use of INTAKE24 in a sample of young people and adults living in Scotland. http://www.foodstandards.gov.scot/sites/default/files/INTAKE24%20FINAL%20REPORT.pdf (accessed July 2017).
52.Thompson, FE, Dixit-Joshi, S, Potischman, N, et al. (2015) Comparison of interviewer-administered and automated self-administered 24-hour dietary recalls in 3 diverse integrated health systems. Am J Epidemiol 181, 970978.
53.Zhu, F, Bosch, M, Khanna, N, et al. (2015) Multiple hypotheses image segmentation and classification with application to dietary assessment. IEEE J Biomed Health Inform 19, 377388.
54.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 2010 IEEE International Symposium on Multimedia, pp. 290–295, 13–15 December 2010, Taichung, Taiwan. http://ieeexplore.ieee.org/document/5693855/ (accessed March 2018).
55.Boushey, C, Delp, EJ & Zhu, FM (2016) Technology Assisted Dietary Assessment. http://www.tadaproject.org (accessed July 2017).
56.Boushey, CJ, Spoden, M, Delp, EJ, et al. (2017) Reported energy intake accuracy compared to doubly labeled water and usability of the mobile food record among community dwelling adults. Nutrients 9, 312.
57.Aflague, TF, Boushey, CJ, Guerrero, RT, et al. (2015) Feasibility and use of the mobile food record for capturing eating occasions among children ages 3–10 years in Guam. Nutrients 7, 44034415.
58.Kerr, DA, Harray, AJ, Pollard, CM, et al. (2016) The Connecting Health and Technology Study: a 6-month randomized controlled trial to improve nutrition behaviours using a mobile food record and text messaging support in young adults. Int J Behav Nutr Phys Act 13, 52.
59.Boushey, CJ, Spoden, M, Zhu, FM, et al. (2017) New mobile methods for dietary assessment: review of image-assisted and image-based dietary assessment methods. Proc Nutr Soc 76, 283294.
60.Statista (2017) Number of smartphone users in the United States from 2010 to 2021 (in millions). https://www.statista.com/statistics/201182/forecast-of-smartphone-users-in-the-us/ (accessed December 2017).
61.Kirkpatrick, SI, Gilsing, AM, Hobin, E, et al. (2017) Lessons from studies to evaluate an online 24-hour recall for use with children and adults in Canada. Nutrients 9, 100.
62.Kirkpatrick, S, Subar, A, Zimmerman, T, et al. (2014) Accuracy of portion size reporting in the Automated Self-Administered 24-hour Recall (ASA24) compared to interviewer-administered recalls. FASEB J 28, no. 1 Supplement, Abstract 36.3.
63.Illner, AK, Freisling, H, Boeing, H, et al. (2012) Review and evaluation of innovative technologies for measuring diet in nutritional epidemiology. Int J Epidemiol 41, 11871203.
64.Kirkpatrick, SI, Subar, AF, Douglass, D, et al. (2014) Performance of the Automated Self-Administered 24-Hour Recall relative to a measure of true intakes and to an interviewer-administered 24-h recall. Am J Clin Nutr 100, 233240.
65.Bradley, J, Simpson, E, Poliakov, I, et al. (2016) Comparison of INTAKE24 (an online 24-h dietary recall tool) with interviewer-led 24-h recall in 11–24 year-old. Nutrients 8, E358.
66.Boushey, CJ, Kerr, DA, Wright, J, et al. (2009) Use of technology in children's dietary assessment. Eur J Clin Nutr 63, Suppl. 1, S50S57.
67.Rangan, AM, Tieleman, L, Louie, JC, et al. (2016) Electronic Dietary Intake Assessment (e-DIA): relative validity of a mobile phone application to measure intake of food groups. Br J Nutr 115, 22192226.
68.Nusser, SM, Carriquiry, AL, Dodd, W, et al. (1996) A semiparametric transformation approach to estimating usual daily intake distributions. J Am Stat Assoc 91, 14401449.
69.Dodd, KW, Guenther, PM, Freedman, LS, et al. (2006) Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc 106, 16401650.
70.Souverein, OW, Dekkers, AL, Geelen, A, et al. (2011) Comparing four methods to estimate usual intake distributions. Eur J Clin Nutr 65, Suppl. 1, S92S101.
71.Lankester, J, Perry, S & Parsonnet, J (2014) Comparison of two methods – regression predictive model and intake shift model – for adjusting self-reported dietary recall of total energy intake of populations. Front Public Health 2, 249.
72.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.
73.Freedman, LS, Commins, JM, Moler, JE, et al. (2014) Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake. Am J Epidemiol 180, 172188.
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