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.

  • Original Communication
  • Published:

Young adolescents' nutrition assessment on computer (YANA-C)

European Journal of Clinical Nutrition volume 59, pages 658–667 (2005)Cite this article

Abstract

Objective:

To assess the relative validity and acceptability of the computerised 24-h recall ‘Young Adolescent's Nutrition Assessment on Computer (YANA-C)’.

Design:

Food and nutrient intakes assessed with YANA-C were compared with food records (study 1) and 24-h dietary recall interviews (study 2).

Main outcome measures:

Intakes of food groups (fruit, fruit juice, vegetables, potatoes, bread, cereals, milk, cheese, other milk products, soft drinks, diet soft drinks, sugar/sweets, pastry/cookies, savoury snacks, butter/sauces, eggs, fish, meat) and nutrients (energy, carbohydrates, protein, fat, fiber, calcium, vitamin C and iron).

Subjects and setting:

A total of 237 pupils (11–14 y) from two primary and four secondary schools (study 1: n=136; study 2: n=101) in Belgium-Flanders.

Results:

YANA-C proved to agree well with both standard methods in categorizing subjects in consumers and nonconsumers (κstudy 1=0.48–0.92; κstudy 2=0.38–0.90). Spearman's correlations for energy and nutrient intakes ranged between 0.44 and 0.79 for study 1 and between 0.44 and 0.86 for study 2. Nutrient and energy intakes were in general (excluding calcium) significantly higher in YANA-C in comparison with the food record, but not in comparison with the interview (only fiber). Statistics used to investigate whether YANA-C agreed with the other methods in ranking portions/amounts in consumers only were fair to moderate for most of the food groups (weighted κ study 1=0.11–0.55; study 2=0.04–0.73); amounts in consumers only, were significantly lower in YANA-C against both standards for cereals; amounts were significantly higher in YANA-C against the food record for milk, soft drinks, sugar/sweets and savoury snacks and against the interview for potatoes. Only a few pupils evaluated the program negatively.

Conclusion:

YANA-C is a promising method to collect detailed dietary information from young adolescents with relatively low staff resources, useful in many nutrition research applications.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Figure 1
Figure 2
Figure 3

Similar content being viewed by others

References

  • Baranowski T, Islam N, Baranowski J, Cullen KW, Myres D, Marsh T & de MC (2002): The food intake recording software system is valid among fourth-grade children. J. Am. Diet. Assoc. 102, 380–385.

    Article  PubMed  Google Scholar 

  • Baxter SD (2003): Accuracy of fourth-graders' dietary recalls of school breakfast and school lunch validated with observations: in-person versus telephone interviews. J. Nutr. Educ. Behav. 35, 124–134.

    Article  PubMed  PubMed Central  Google Scholar 

  • Baxter SD, Thompson WO, Davis HC & Johnson MH (1997): Impact of gender, ethnicity, meal component, and time interval between eating and reporting on accuracy of fourth-graders' self-reports of school lunch. J. Am. Diet. Assoc. 97, 1293–1298.

    Article  CAS  PubMed  Google Scholar 

  • Baxter SD, Thompson WO, litaker MS, Frye FH & Guinn CH (2002): Low accuracy and low consistency of fourth-graders' school breakfast and school lunch recalls. J. Am. Diet. Assoc. 102, 386–395.

    Article  PubMed  PubMed Central  Google Scholar 

  • Baxter SD, Smith AF, litaker MS, Guinn CH, Shaffer NM, Baglio ML & Frye FH (2004): Recency affects reporting accuracy of children's dietary recalls. Ann. Epidemiol. 14, 385–390.

    Article  PubMed  Google Scholar 

  • Bingham SA (1991): Assessment of food consumption and nutrient intake: Current intake. In Design Concepts in Nutritional Epidemiology eds BM Margetts & M Nelson, pp 154–167. New York: Oxford University Press.

    Google Scholar 

  • Bingham SA, Nelson M, Paul AA, Halaldsdottir J, Loken EB & Van Staveren WA (1988): Methods for data collection at an individual level. In Manual on Methodology for Food Consumption Studies eds ME Cameron & WA Van Staveren, pp 53–106. Oxford: Oxford University Press.

    Google Scholar 

  • Bland JM & Altman DG (1986): Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1, 307–310.

    Article  CAS  PubMed  Google Scholar 

  • Buzzard IM, Faucett CL, Jeffery RW, McBane L, McGovern P, Baxter JS, Shapiro AC, Blackburn GL, Chlebowski RT, Elashoff RM & Wynder EL (1996): Monitoring dietary change in a low-fat diet intervention study: advantages of using 24-hour dietary recalls vs food records. J. Am. Diet. Assoc. 96, 574–579.

    Article  CAS  PubMed  Google Scholar 

  • Cade J, Thompson R, Burley V & Warm D (2002): Development, validation and utilisation of food-frequency questionnaires—a review. Public Health Nutr. 5, 567–587.

    Article  PubMed  Google Scholar 

  • Centers for Disease Control and Prevention (1997): Guidelines for school health programs to promote lifelong healthy eating. J. Sch. Health 67, 9–26.

  • Crawford PB, Obarzanek E, Morrison J & Sabry ZI (1994): Comparative advantage of 3-day food records over 24-hour recall and 5-day food frequency validated by observation of 9- and 10-year-old girls. J. Am. Diet. Assoc. 94, 626–630.

    Article  CAS  PubMed  Google Scholar 

  • Domel SB, Thompson WO, Baranowski T & Smith AF (1994): How children remember what they have eaten. J. Am. Diet. Assoc. 94, 1267–1272.

    Article  CAS  PubMed  Google Scholar 

  • Edmunds LD & Ziebland S (2002): Development and validation of the Day in the Life Questionnaire (DILQ) as a measure of fruit and vegetable questionnaire for 7–9 year olds. Health Educ. Res. 17, 211–220.

    Article  CAS  PubMed  Google Scholar 

  • Health Council Belgium (1997): Household Weights and Measures; A Manual for a Standardised Quantification of Food Items in Belgium. Brussels, Ministry of Public Health.

  • Klaver W, Burema J, Van Staveren WA & Knuiman JT (1988): Definitions of terms. In Manual on Methodology for Food Consumption Studies eds ME Cameron & WA Van Staveren, pp 11–23. Oxford: Oxford University Press.

    Google Scholar 

  • Kramer MS & Feinstein AR (1981): Clinical biostatistics. LIV. The biostatistics of concordance [published erratum appears in Clin Pharmacol Ther 1989;46(3):309]. Clin. Pharmacol. Ther. 29, 111–123.

    Article  CAS  PubMed  Google Scholar 

  • Livingstone MB & Robson PJ (2000): Measurement of dietary intake in children. Proc. Nutr. Soc. 59, 279–293.

    Article  CAS  PubMed  Google Scholar 

  • Lytle LA, Nichaman MZ, Obarzanek E, Glovsky E, Montgomery D, Nicklas T, Zive M & Feldman H (1993): Validation of 24-hour recalls assisted by food records in third-grade children. The CATCH Collaborative Group. J. Am. Diet. Assoc. 93, 1431–1436.

    Article  CAS  PubMed  Google Scholar 

  • Lytle LA, Murray DM, Perry CL & Eldridge AL (1998): Validating fourth-grade students' self-report of dietary intake: results from the 5 A Day Power Plus program. J. Am. Diet. Assoc. 98, 570–572.

    Article  CAS  PubMed  Google Scholar 

  • Masson LF, McNeill G, Tomany JO, Simpson JA, Peace HS, Wei L, Grubb DA & Bolton-Smith C (2003): Statistical approaches for assessing the relative validity of a food-frequency questionnaire: use of correlation coefficients and the kappa statistic. Public Health Nutr. 6, 313–321.

    Article  CAS  PubMed  Google Scholar 

  • Matthys C, De Henauw S, Devos C & De Backer G (2003): Estimated energy intake, macronutrient intake and meal pattern of Flemish adolescents. Eur. J. Clin. Nutr. 57, 366–375.

    Article  CAS  PubMed  Google Scholar 

  • Mcpherson RS, Hoelscher DM, Alexander M, Scanlon KS & Serdula MK (2000): Dietary assessment methods among school-aged children: validity and reliability. Prev. Med. 31, s11–s33.

    Article  Google Scholar 

  • Mullenbach V, Kushi LH, Jacobson C, Gomez-Marin O, Prineas RJ, Roth-Yousey L & Sinaiko AR (1992): Comparison of 3-day food record and 24-hour recall by telephone for dietary evaluation in adolescents. J. Am. Diet. Assoc. 92, 743–745.

    CAS  PubMed  Google Scholar 

  • NEVO (1996): NEVO Tabel. Nederlands voedingsstoffenbestand. The Netherlands: Velotekst, Den Haag.

  • NUBEL (1999): Belgische voedingsmiddelentabel 3rd edition. Brussels, Belgium, Ministry of Public Health.

  • Prochaska JJ & Sallis J (2004): Reliability and validity of a fruit and vegetable screening measure for adolescents. J. Adolesc. Health 34, 163–165.

    Article  PubMed  Google Scholar 

  • Samuelson G (1970): An epidemiological study of child health and nutrition in a northern Swedish County. II. Methodological study of the recall technique. Nutr. Metab. 12, 321–340.

    Article  CAS  PubMed  Google Scholar 

  • Spear BA (2002): Adolescent growth and development. J. Am. Diet. Assoc. 102, S23–S29.

    Article  PubMed  Google Scholar 

  • Thompson FE & Byers T (1994): Dietary assessment resource manual. J. Nutr. 124, 2245S–2317S.

    CAS  PubMed  Google Scholar 

  • Unilever Becel Nutrient Calculation Program 5.03 (1995): Hartog Union and Van den Bergh, the Netherlands.

  • Van Horn LV, Gernhofer N, Moag-Stahlberg A, Farris R, Hartmuller G, Lasser VI, Stumbo P, Craddick S & Ballew C (1990): Dietary assessment in children using electronic methods: telephones and tape recorders. J. Am. Diet. Assoc. 90, 412–416.

    CAS  PubMed  Google Scholar 

  • Weber JL, Lytle L, Gittelsohn J, Cunningham-Sabo L, Heller K, Anliker JA, Stevens J, Hurley J & Ring K (2004): Validity of self-reported dietary intake at school meals by American Indian children: the Pathways Study. J. Am. Diet. Assoc. 104, 746–752.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Mieke De Maeyer for her advice in grouping the food items, Annelore Van Speybroeck and Florien Van Laere from the Department of Health Sciences, Vesalius – Hogeschool Gent, for their assistance with data collection, as well as the school principals, teachers and pupils who agreed to participate in the study.

Author information

Author notes

  1. M Covents: Private consultant.

Authors and Affiliations

  1. Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium

    C A Vereecken, C Matthys & L Maes

Authors
  1. C A Vereecken
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. M Covents
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. C Matthys
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. L Maes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C A Vereecken.

Additional information

Guarantor: CA Vereecken.

Contributors: CAV and MC developed the program. CAV designed the study, analysed and interpreted the data and wrote the manuscript. CM provided information on food items to be used based on previous research. LM supervised the study. MC, CM and LM gave comments upon the manuscript.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Vereecken, C., Covents, M., Matthys, C. et al. Young adolescents' nutrition assessment on computer (YANA-C). Eur J Clin Nutr 59, 658–667 (2005). https://doi.org/10.1038/sj.ejcn.1602124

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.ejcn.1602124

Keywords

This article is cited by

Search

Advanced search

Quick links