Reproducibility and feasibility of an online self-administered food frequency questionnaire for use among adult Norwegians

  • Monica Hauger Carlsen Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
  • Lene Frost Andersen Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
  • Anette Hjartåker Department of Nutrition, Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Norway
Keywords: Online dietary assessment, test–retest, nutrient intake, food intake


Background: New methods of dietary assessment are increasingly making use of online technologies. The development of a new online food frequency questionnaire warranted investigation of its feasibility and the reproducibility of its results.

Objective: To investigate the feasibility and reproducibility of a newly developed online FFQ (WebFFQ).

Design: The semiquantitative WebFFQ was designed to assess the habitual diet the previous year, with questions about frequency of intake and portion sizes. Estimations of portion sizes include both pictures and household measures, depending on the type of food in question. In two independent cross-sectional studies conducted in 2015 and 2016, adults were recruited by post following random selection from the general population. In the first study, participants (n = 229) filled in the WebFFQ and answered questions about its feasibility, and in two subsequent focus group meetings, participants (n = 9) discussed and gave feedback about the feasibility of the WebFFQ. In the second study, the WebFFQ’s reproducibility was assessed by asking participants (n = 164) to fill it in on two separate occasions, 12 weeks apart. Moreover, in the second study, participants were offered personal dietary feedback, a monetary gift certificate, or both, as incentives to complete the study.

Results: In the feasibility study, evaluation form results showed that participants raised issues regarding the estimation of portion size and the intake of seasonal foods as being particularly challenging; furthermore, in the focus group discussions, personal feedback on diet was perceived to be a more motivating factor than monetary reward. In the reproducibility study, total food intake was lower in the second WebFFQ; however, 63% of the food groups were not significantly different from those in the first WebFFQ. Correlations of food intake ranged from 0.62 to 0.90, >86% of the participants were classified into the same or adjacent quartiles, and misclassification ranged from 0 to 3%. Average energy intake was 3.5% lower (p = 0.001), fiber showed the least difference at 1.6% (p = 0.007), and sugar intake differed the most at −6.8% (borderline significant, p = 0.08). Percentage energy obtained from macronutrients did not differ significantly between the first and second WebFFQs.

Conclusion: Our results suggest that at group level, the WebFFQ showed good reproducibility for the estimations of intake of food groups, energy, and nutrients. The feasibility of the WebFFQ is good; however, revisions to further improve portion size estimations should be included in future versions. The WebFFQ is considered suitable for dietary assessments for healthy adults in the Norwegian population.


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  1. Cade JE, Warthon-Medina M, Albar S, Alwan NA, Ness A, Roe M, et al. DIET@NET: best practice guidelines for dietary assessment in health research. BMC Med 2017; 15: 202–17. doi: 10.1186/s12916-017-0962-x

  2. Lovegrove JA, Hodson L, Sharma S, Lanham-New SA. Nutrition research methodologies. Chichester: John Wiley & Sons; 2015. ISBN: 978-1-11---8-55467-8.

  3. Amoutzopoulos B, Steer T, Roberts C, Cade JE, Boushey CJ, Collins CE, et al. 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. J Nutr Sci 2018; 7: e11. doi: 10.1017/jns.2018.4

  4. Cade JE. Measuring diet in the 21st century: use of new technologies. Proc Nutr Soc 2017; 76(3): 276–82. doi: 10.1017/S0029665116002883

  5. Margetts B, Nelson M. Design concepts in nutritional epidemiology. 2nd ed. New York: Oxford University Press; 2003. ISBN: 978-0192627391.

  6. Andersen LF, Solvoll K, Johansson LR, Salminen I, Aro A, Drevon CA. Evaluation of a food frequency questionnaire with weighed records, fatty acids, and alpha-tocopherol in adipose tissue and serum. Am J Epidemiol 1999; 150(1): 75–87. doi: 10.1093/oxfordjournals.aje.a009921

  7. Carlsen MH, Lillegaard IT, Karlsen A, Blomhoff R, Drevon CA, Andersen LF. Evaluation of energy and dietary intake estimates from a food frequency questionnaire using independent energy expenditure measurement and weighed food records. Nutr J 2010; 9: 37. doi: 10.1186/1475-2891-9-37

  8. Medin AC, Carlsen MH, Hambly C, Speakman JR, Strohmaier S, Andersen LF. The validity of a web-based FFQ assessed by doubly labelled water and multiple 24-h recalls. Br J Nutr 2017; 118(12): 1106–17. doi: 10.1017/S0007114517003178

  9. Rimestad AH, Løken EB, Nordbotten A. The Norwegian food composition table and the database for nutrient calculations at the Institute of Nutrition Reserach. Nor J Epidemiol 2000; 10(1): 7–16. doi: 10.5324/nje.v10i1.509

  10. Bland M. An introduction to medical statistics. Oxford: Oxford University Press; 2015. ISBN: 978-0-19-958992-0.

  11. Cade J, Thompson R, Burley V, Warm D. Development, validation and utilisation of food-frequency questionnaires –a review. Public Health Nutr 2002; 5(4): 567–87. doi: 10.1079PHN2001318

  12. Carlsen MH, Karlsen A, Lillegaard IT, Gran JM, Drevon CA, Blomhoff R, et al. Relative validity of fruit and vegetable intake estimated from an FFQ, using carotenoid and flavonoid biomarkers and the method of triads. Br J Nutr 2011; 105(10): 1530–8. doi: 10.1017/S0007114510005246

  13. Henriksen HB, Carlsen MH, Paur I, Berntsen S, Bohn SK, Skjetne AJ, et al. Relative validity of a short food frequency questionnaire assessing adherence to the Norwegian dietary guidelines among colorectal cancer patients. Food Nutr Res 2018; 62. doi: 10.29219/fnr.v62.1306

  14. Beasley JM, Davis A, Riley WT. Evaluation of a web-based, pictorial diet history questionnaire. Public health Nutr 2009; 12(5): 651–9. doi: 10.1017/S1368980008002668

  15. Kristal AR, Kolar AS, Fisher JL, Plascak JJ, Stumbo PJ, Weiss R, et al. Evaluation of web-based, self-administered, graphical food frequency questionnaire. J Acad Nutr Diet 2014; 114(4): 613–21. doi: 10.1016/j.jand.2013.11.017

  16. Labonte ME, Cyr A, Baril-Gravel L, Royer MM, Lamarche B. Validity and reproducibility of a web-based, self-administered food frequency questionnaire. Eur J Clin Nutr 2012; 66(2): 166–73. doi: 10.1038/ejcn.2011.163

  17. Vereecken CA, De Bourdeaudhuij I, Maes L. The HELENA online food frequency questionnaire: reproducibility and comparison with four 24-h recalls in Belgian-Flemish adolescents. Eur J Clin Nutr 2010; 64(5): 541–8. doi: 10.1038/ejcn.2010.24

  18. Faulkner GP, Livingstone MBE, Pourshahidi LK, Spence M, Dean M, O’Brien S, et al. An evaluation of portion size estimation aids: consumer perspectives on their effectiveness. Appetite 2017; 114: 200–8. doi: 10.1016/j.appet.2017.03.027

  19. Dahl L, Maeland CA, Bjorkkjaer T. A short food frequency questionnaire to assess intake of seafood and n-3 supplements: validation with biomarkers. Nutr J 2011; 10: 127. doi: 10.1186/1475-2891-10-127

  20. Liu L, Wang PP, Roebothan B, Ryan A, Tucker CS, Colbourne J, et al. Assessing the validity of a self-administered food-frequency questionnaire (FFQ) in the adult population of Newfoundland and Labrador, Canada. Nutr J 2013; 12: 49. doi: 10.1186/1475-2891-12-49

  21. Galea S, Tracy M. Participation rates in epidemiologic studies. Ann Epidemiol 2007; 17(9): 643–53. doi: 10.1016/j.annepidem.2007.03.013

  22. Halbesleben JR, Whitman MV. Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias. Health Serv Res 2013; 48(3): 913–30. doi: 10.1111/1475-6773.12002

  23. Keeble CB, P.D.; Barber,S.; Law,G.R. Participation rates in epidemiology studies and surveys: a reveiw 2007–2015. Internet J Epidemiol 2015; 14(1): 1–14. doi: 10.5580/IJE.34897

  24. Edwards P, Cooper R, Roberts I, Frost C. Meta-analysis of randomised trials of monetary incentives and response to mailed questionnaires. J Epidemiol Community Health 2005; 59(11): 987–99. doi: 10.1136/jech.2005.034397

  25. Edwards PJ, Roberts I, Clarke MJ, Diguiseppi C, Wentz R, Kwan I, et al. Methods to increase response to postal and electronic questionnaires. Cochrane Database Syst Rev 2009; (3): MR000008. doi: 10.1002/14651858.MR000008.pub4

  26. Myhre JB, Andersen LF, Holvik K, Astrup H, Kristiansen AL. Means of increasing response rates in a Norwegian dietary survey among infants – results from a pseudo-randomized pilot study. BMC Med Res Methodol 2019; 19(1): 144. doi: 10.1186/s12874-019-0789-6

  27. Statistics Norway. Available from: statbank [cited 29 Dec 2020].

  28. Fallaize R, Forster H, Macready AL, Walsh MC, Mathers JC, Brennan L, et al. Online dietary intake estimations: reproducibility and validity of the Food4Me frequenncy questionnaire against a 4-day weighed food record. J Med Internet Res 2014; 16(8): e190. doi: 10.2196/jmir.3355

  29. Parr CL, Veierod MB, Laake P, Lund E, Hjartaker A. Test-retest reproducibility of a food frequency questionnaire (FFQ) and estimated effects on disease risk in the Norwegian Women and Cancer Study (NOWAC). Nutr J 2006; 5: 4. doi: 10.1186/1475-2891-5-4

  30. Shu XO, Yang G, Jin F, Liu D, Kushi L, Wen W, et al. Validity and reproducibility of the food frequency questionnaire used in the Shanghai Women’s Health Study. Eur J Clin Nutr 2004; 58(1): 17–23. doi: 10.1038/sj.ejcn.1601738

  31. Tollosa DN, Van Camp J, Huybrechts I, Huybregts L, Van Loco J, De Smet S, et al. Validity and reproducibility of a food frequency questionnaire for dietary factors related to colorectal cancer. Nutrients 2017; 9(11): 1257. doi: 10.3390/nu9111257

  32. Villegas R, Yang G, Liu D, Xiang YB, Cai H, Zheng W, et al. Validity and reproducibility of the food-frequency questionnaire used in the Shanghai men’s health study. Br J Nutr 2007; 97(5): 993–1000. doi: 10.1017/S0007114507669189

  33. Willett W. Nutritional epidemiology. 2nd ed. Oxford: Oxford University Press; 1998. ISBN: 9780195122978.

  34. Thompson AK, Subar AF. Assessment methods for research and practice. In: Coulston AM, Boushey CJ, Ferruzzi M, Delahanty LM, eds. Nutrition in the prevention and treatment of disease. 4th ed. London: Elsevier; 2017, pp. 5–48. eBook ISBN: 9780128029473, ISBN: 9780128029282.

  35. Black AE. Critical evaluation of energy intake using teh Goldberg cut-off for energy intake: basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obesity 2000; 24: 1119–30. doi: 10.1038/sj.ijo.0801376

  36. Lundblad MW, Andersen LF, Jacobsen BK, Carlsen MH, Hjartaker A, Grimsgaard S, et al. Energy and nutrient intakes in relation to national nutrition recommendations in a Norwegian population-based sample: the Tromso Study 2015–16. Food Nutr Res 2019; 63: 3616. doi: 10.29219/fnr.v63.3616

How to Cite
Hauger Carlsen, M., Frost Andersen, L., & Hjartåker, A. (2021). Reproducibility and feasibility of an online self-administered food frequency questionnaire for use among adult Norwegians. Food & Nutrition Research, 65.
Original Articles