Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Epidemiology

Evaluation of a short food frequency questionnaire for dietary intake assessment among children

Abstract

Background/objectives

The objective of this study was to evaluate the performance of a short food frequency questionnaire (FFQ) to assess dietary intake at 4 and 7 years of age, against 3d food diaries (FD) and serum biomarkers, using two methods to convert the FFQ to daily intake in grams and nutrients (standard and z-score method).

Subjects/methods

The present analysis comprises data from 2482 4-year-old children and 3511 7-year-old children, from the birth cohort Generation XXI (Porto, Portugal). To estimate daily consumption from the FFQ, the frequency response was multiplied by a standard mean portion (standard method) or adjusted with data from the FD (z-score method). The dietary intake obtained from the FFQ was compared with the FD and serum biomarkers, using Intra-Class Correlation Coefficients (ICC), de-attenuated Pearson’s correlation coefficients and Bland Altman analysis.

Results

In general, the mean daily food intake estimated by the z-score method had a higher agreement with the FD, than the standard method. The highest ICC was obtained for “vegetable soup” (ICC = 0.536), using the z-score method, compared to an ICC of 0.373 using the standard method. Significant correlation coefficients were observed for all nutrients; the average of correlation coefficients was 0.39 at 4 years and 0.42 at 7 years of age. For the majority of nutrients, the correlation between mean and mean difference was lower using the z-score method, in comparison with the standard method.

Conclusions

The results suggest that the FFQ is a reasonably good instrument to estimate dietary intake in children. Moreover, adjusting the FFQ portion size, by using a z-score method, seems to increase the accuracy of dietary data in children.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1

Similar content being viewed by others

References

  1. Rutishauser IH. Dietary intake measurements. Public Health Nutr. 2005;8(7a):1100–7.

    PubMed  Google Scholar 

  2. Ribas-Barba L, Serra-Majem L, Roman-Vinas B, Ngo J, Garcia-Alvarez A. Effects of dietary assessment methods on assessing risk of nutrient intake adequacy at the population level: from theory to practice. Br J Nutr. 2009;101(Suppl 2):S64–72.

    CAS  PubMed  Google Scholar 

  3. Burrows TL, Martin RJ, Collins CE. A systematic review of the validity of dietary assessment methods in children when compared with the method of doubly labeled water. J Am Diet Assoc. 2010;110:1501–10.

    PubMed  Google Scholar 

  4. Gonzalez CA. The European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr. 2006;9(1a):124–6.

    PubMed  Google Scholar 

  5. Flood A, Rastogi T, Wirfalt E, Mitrou PN, Reedy J, Subar AF, et al. Dietary patterns as identified by factor analysis and colorectal cancer among middle-aged Americans. Am J Clin Nutr. 2008;88:176–84.

    Article  CAS  PubMed  Google Scholar 

  6. Linos E, Willett WC, Cho E, Colditz G, Frazier LA. Red meat consumption during adolescence among premenopausal women and risk of breast cancer. Cancer Epidemiol Biomark Prev. 2008;17:2146–51.

    Google Scholar 

  7. Leermakers ET, Felix JF, Erler NS, Cerimagic A, Wijtzes AI, Hofman A, et al. Sugar-containing beverage intake in toddlers and body composition up to age 6 years: The Generation R study. Eur J Clin Nutr. 2015;69:314–21.

    CAS  PubMed  Google Scholar 

  8. Bell LK, Golley RK, Magarey AM. Short tools to assess young children’s dietary intake: a systematic review focusing on application to dietary index research. J Obes. 2013;2013:709626.

    PubMed  PubMed Central  Google Scholar 

  9. Roman-Vinas B, Ortiz-Andrellucchi A, Mendez M, Sanchez-Villegas A, Pena Quintana L, Aznar LA, et al. Is the food frequency questionnaire suitable to assess micronutrient intake adequacy for infants, children and adolescents? Matern Child Nutr. 2010;6(Suppl 2):112–21.

    PubMed  PubMed Central  Google Scholar 

  10. Lillegaard IT, Overby NC, Andersen LF. Evaluation of a short food frequency questionnaire used among Norwegian children. Food Nutr Res. 2012;56:6399–6408.

    Google Scholar 

  11. Corella D, Ordovas JM. Biomarkers: background, classification and guidelines for applications in nutritional epidemiology. Nutr Hosp. 2015;31(Suppl 3):177–88.

    PubMed  Google Scholar 

  12. Vioque J, Gimenez-Monzo D, Navarrete-Munoz EM, Garcia-de-la-Hera M, Gonzalez-Palacios S, Rebagliato M, et al. Reproducibility and validity of a food frequency questionnaire designed to assess diet in children aged 4–5 years. PLoS ONE. 2016;11:e0167338.

    PubMed  PubMed Central  Google Scholar 

  13. Prentice RL, Tinker LF, Huang Y, Neuhouser ML. Calibration of self-reported dietary measures using biomarkers: an approach to enhancing nutritional epidemiology reliability. Curr Atheroscler Rep. 2013;15:353.

    PubMed  Google Scholar 

  14. Freedman LS, Commins JM, Moler JE, Arab L, Baer DJ, Kipnis V, et al. Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake. Am J Epidemiol. 2014;180:172–88.

    PubMed  PubMed Central  Google Scholar 

  15. Cade J, Thompson R, Burley V, Warm D. Development, validation and utilisation of food-frequency questionnaires—a review. Public Health Nutr. 2002;5:567–87.

    PubMed  Google Scholar 

  16. Koster-Rasmussen R, Siersma V, Halldorsson TI, de Fine Olivarius N, Henriksen JE, Heitmann BL. Missing portion sizes in FFQ--alternatives to use of standard portions. Public Health Nutr. 2015;18:1914–21.

    PubMed  Google Scholar 

  17. Pfrimer K, Sartorelli DS, Rosa FT, Mendes Resende CM, Viera DV, Rabito EI, et al. Calibration of the food list and portion sizes of a food frequency questionnaire applied to free-living elderly people. Nutrition. 2013;29:760–4.

    PubMed  Google Scholar 

  18. Nothlings U, Hoffmann K, Bergmann MM, Boeing H. Fitting portion sizes in a self-administered food frequency questionnaire. J Nutr. 2007;137:2781–6.

    PubMed  Google Scholar 

  19. Lambe J, Kearney J, Leclercrq C, Berardi D, Zunft HF, Sulzer S, et al. Enhancing the capacity of food consumption surveys of short duration to estimate long-term consumer-only intakes by combination with a qualitative food frequency questionnaire. Food Addit Contam. 2000;17:177–87.

    CAS  PubMed  Google Scholar 

  20. Day N, McKeown N, Wong M, Welch A, Bingham S. Epidemiological assessment of diet: a comparison of a 7-day diary with a food frequency questionnaire using urinary markers of nitrogen, potassium and sodium. Int J Epidemiol. 2001;30:309–17.

    CAS  PubMed  Google Scholar 

  21. Larsen PS, Kamper-Jorgensen M, Adamson A, Barros H, Bonde JP, Brescianini S, et al. Pregnancy and birth cohort resources in europe: a large opportunity for aetiological child health research. Paediatr Perinat Epidemiol. 2013;27:393–414.

    PubMed  Google Scholar 

  22. WHO Multicentre Growth Reference Study Group. WHO Child Growth Standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: methods and development. Geneva: WHO; 2006.

    Google Scholar 

  23. Vilela S, Oliveira A, Pinto E, Moreira P, Barros H, Lopes C. The influence of socioeconomic factors and family context on energy-dense food consumption among 2-year-old children. Eur J Clin Nutr. 2015;69:47–54.

    CAS  PubMed  Google Scholar 

  24. Durao C, Andreozzi V, Oliveira A, Moreira P, Guerra A, Barros H, et al. Maternal child-feeding practices and dietary inadequacy of 4-year-old children. Appetite. 2015;92:15–23.

    PubMed  Google Scholar 

  25. Moreira T, Severo M, Oliveira A, Ramos E, Rodrigues S, Lopes C. Eating out of home and dietary adequacy in preschool children. Br J Nutr. 2015;114:297–305.

    CAS  PubMed  Google Scholar 

  26. U.S. Department of Agriculture, Agricultural Research Service. USDA National Nutrient Database For Standard Reference. Baltimore, MD: USDA; 2003.

  27. Lopes C, Aro A, Azevedo A, Ramos E, Barros H. Intake and adipose tissue composition of fatty acids and risk of myocardial infarction in a male Portuguese community sample. J Am Diet Assoc. 2007;107:276–86.

    CAS  PubMed  Google Scholar 

  28. Bel-Serrat S, Mouratidou T, Pala V, Huybrechts I, Bornhorst C, Fernandez-Alvira JM, et al. Relative validity of the Children’s Eating Habits Questionnaire-food frequency section among young European children: the IDEFICS Study. Public Health Nutr. 2014;17:266–76.

    PubMed  Google Scholar 

  29. Matos SM, Prado MS, Santos CA, D’Innocenzo S, Assis AM, Dourado LS, et al. Validation of a food frequency questionnaire for children and adolescents aged 4 to 11 years living in Salvador, Bahia. Nutr Hosp. 2012;27:1114–9.

    CAS  PubMed  Google Scholar 

  30. Vereecken CA, Maes L. A Belgian study on the reliability and relative validity of the health behaviour in school-aged children food-frequency questionnaire. Public Health Nutr. 2003;6:581–8.

    PubMed  Google Scholar 

  31. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33:159–74.

    CAS  PubMed  Google Scholar 

  32. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986;1:307–10.

    CAS  PubMed  Google Scholar 

  33. Cohen J. A power primer. Psychol Bull. 1992;112:155–9.

    CAS  PubMed  Google Scholar 

  34. Lillegaard ITL, Øverby NC, Andersen LF. Evaluation of a short food frequency questionnaire used among Norwegian children. Food Nutr Res. 2012. https://doi.org/10.3402/fnr.v56i0.6399.

    Google Scholar 

  35. Lovell A, Bulloch R, Wall CR, Grant CC. Quality of food-frequency questionnaire validation studies in the dietary assessment of children aged 12 to 36 months: a systematic literature review. J Nutr Sci. 2017;6:e16.

    PubMed  PubMed Central  Google Scholar 

  36. Institute of Medicine. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty accids, cholesterol, protein and amino acids. Washigton, DC: National Acadamy Press; 2002/2005.

  37. Institute of Medicine. Dietary reference intakes for calcium, phosphorous, magnesium, vitamin D, and fluoride. Washigton DC: National Acadamy Press; 1997.

    Google Scholar 

  38. Kowalkowska J, Slowinska MA, Slowinski D, Dlugosz A, Niedzwiedzka E, Wadolowska L. Comparison of a full food-frequency questionnaire with the 3-day unweighted food records in young Polish adult women: implications for dietary assessment. Nutrients. 2013;5:2747–76.

    PubMed  PubMed Central  Google Scholar 

  39. Leon Guerrero RT, Chong M, Novotny R, Wilkens LR, Badowski G, Blas-Laguana M, et al. Relative validity and reliability of a quantitative food frequency questionnaire for adults in Guam. Food Nutr Res. 2015;59:26276.

    PubMed  Google Scholar 

  40. Sahashi Y, Tsuji M, Wada K, Tamai Y, Nakamura K, Nagata C. Validity and reproducibility of food frequency questionnaire in Japanese children aged 6 years. J Nutr Sci Vitaminol (Tokyo). 2011;57:372–6.

    CAS  Google Scholar 

  41. Fox MK, Devaney B, Reidy K, Razafindrakoto C, Ziegler P. Relationship between portion size and energy intake among infants and toddlers: evidence of self-regulation. J Am Diet Assoc. 2006;106(Suppl 1):S77–83.

    PubMed  Google Scholar 

  42. Brogden N, Almiron-Roig E. Estimated portion sizes of snacks and beverages differ from reference amounts and are affected by appetite status in non-obese men. Public Health Nutr. 2011;14:1743–51.

    PubMed  Google Scholar 

  43. Brunstrom JM, Rogers PJ, Pothos EM, Calitri R, Tapper K. Estimating everyday portion size using a ‘method of constant stimuli’: in a student sample, portion size is predicted by gender, dietary behaviour, and hunger, but not BMI. Appetite. 2008;51:296–301.

    PubMed  Google Scholar 

  44. Burger KS, Kern M, Coleman KJ. Characteristics of self-selected portion size in young adults. J Am Diet Assoc. 2007;107:611–8.

    PubMed  Google Scholar 

  45. Smith AF, Baxter SD, Hitchcock DB, Finney CJ, Royer JA, Guinn CH. Cognitive ability, social desirability, body mass index and socioeconomic status as correlates of fourth-grade children’s dietary-reporting accuracy. Eur J Clin Nutr. 2016;70:1028–33.

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Croker H, Sweetman C, Cooke L. Mothers’ views on portion sizes for children. J Hum Nutr Diet. 2009;22:437–43.

    CAS  PubMed  Google Scholar 

  47. Palaniappan U, Cue RI, Payette H, Gray-Donald K. Implications of day-to-day variability on measurements of usual food and nutrient intakes. J Nutr. 2003;133:232–5.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the families enrolled in Generation XXI for their kindness, all members of the research team for their enthusiasm and perseverance and the participating hospitals and their staff for their help and support. The authors acknowledge the support from the Epidemiology Research Unit (EPI-Unit: UID-DTP/04750/2013). We gratefully acknowledge Dr Tiago Guimarães and Dr Isaac Barroso from the Department of Clinical Pathology of São João Hospital Center (Porto), and Daniela Ferreira from the Institute of Public Health of the University of Porto, for analyzing the serum biomarkers.

Author contributions

SV contributed to the design of study, performed statistical analyses and interpretation of the data and wrote the first draft of the paper. MS contributed the statistical analysis and to the interpretation of data. TM and ER contributed to the design of data collection instruments and contributed to the interpretation of data. CL contributed to the design of study, coordinated the design of data collection instruments and contributed to the discussion of results. All the authors critically reviewed the manuscript and approved the final version as submitted.

Funding

Generation XXI was funded by the Health Operational Programme—Saúde XXI, Community Support Framework III and the Regional Department of Ministry of Health. It was supported by the Calouste Gulbenkian Foundation, by FEDER from the Operational Programme Factors of Competitiveness—COMPETE and through national funding from the Foundation for Science and Technology – FCT (Portuguese Ministry of Education and Science) under the project PTDC/SAU-EPI/121532/2010 (FEDER-Operational Programme Factors of Competitiveness—COMPETE—FCOMP-01–0124-FEDER-021177), and the PhD Grant SFRH/BD/92389/2013 (SV).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sofia Vilela.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Food diaries and FFQ’s mean and s.d. of food intake at 4 and 7 years of age

41430_2018_200_MOESM2_ESM.docx

Intraclass correlation coefficients (ICC), Bland Altman analysis and Cohen effect size between daily intakes of energy and nutrients from the food diaries and FFQ (standardmethod) at 4 and 7 years of

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vilela, S., Severo, M., Moreira, T. et al. Evaluation of a short food frequency questionnaire for dietary intake assessment among children. Eur J Clin Nutr 73, 679–691 (2019). https://doi.org/10.1038/s41430-018-0200-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41430-018-0200-4

This article is cited by

Search

Quick links