Skip to main content

Advertisement

Log in

Urinary sucrose and fructose to validate self-reported sugar intake in children and adolescents: results from the I.Family study

  • Original Contribution
  • Published:
European Journal of Nutrition Aims and scope Submit manuscript

Abstract

Purpose

Excessive consumption of free sugar increases the risk for non-communicable diseases where a proper assessment of this intake is necessary to correctly estimate its association with certain diseases. Urinary sugars have been suggested as objective biomarkers for total and free sugar intake in adults but less is known about this marker in children and adolescents. Therefore, the aim of this exploratory study is to evaluate the relative validity of self-reported intake using urinary sugars in children and adolescents.

Methods

The study was conducted in a convenience subsample of 228 participants aged 5–18 years of the I.Family study that investigates the determinants of food choices, lifestyle and health in European families. Total, free and intrinsic sugar intake (g/day) and sugar density (g/1000 kcal) were assessed using 24-h dietary recalls (24HDRs). Urinary sucrose (USUC) and urinary fructose (UFRU) were measured in morning urine samples and corrected for creatinine excretion (USUC/Cr, UFRU/Cr). Correlation coefficients, the method of triads and linear regression models were used to investigate the relationship between intake of different types of sugar and urinary sugars.

Results

The correlation between usual sugar density calculated from multiple 24HDRs and the sum of USUC/Cr and UFRU/Cr (USUC/Cr + UFRU/Cr) was 0.38 (p < 0.001). The method of triads revealed validity coefficients for the 24HDR from 0.64 to 0.87. Linear regression models showed statistically significant positive associations between USUC/Cr + UFRU/Cr and the intake of total and free sugar.

Conclusions

These findings support the relative validity of total and free sugar intake assessed by self-reported 24HDRs in children and adolescents.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

References

  1. World Health Organization (2015) Guideline: sugars intake for adults and children. WHO, Geneva

    Google Scholar 

  2. World Health Organization (2003) Joint WHO/FAO expert consultation. Diet, nutrition and the prevention of chronic diseases. WHO, Geneva

    Google Scholar 

  3. World Cancer Research Fund/American Institute for Cancer Research (2007) Food, nutrition, physical activity, and the prevention of cancer: a global perspective. AIRC, Washington, D.C.

    Google Scholar 

  4. World Cancer Research Fund/American Institute for Cancer Research (2017) Our Cancer Prevention Recommendations. http://www.wcrf.org/int/research-we-fund/our-cancer-prevention-recommendations/. Accessed 29 Nov 2017

  5. Svensson Å, Larsson C, Eiben G, Lanfer A, Pala V, Hebestreit A, Huybrechts I, Fernández-Alvira J, Russo P, Koni A, De Henauw S, Veidebaum T, Molnár D, Lissner L, on behalf of the IDEFICS consortium (2014) European children’s sugar intake on weekdays versus weekends: the IDEFICS study. Eur J Clin Nutr 68:822–828

    Article  CAS  PubMed  Google Scholar 

  6. Livingstone M, Robson P (2000) Measurement of dietary intake in children. Proc Nutr Soc 59:279–293

    Article  CAS  PubMed  Google Scholar 

  7. Börnhorst C, Huybrechts I, Hebestreit A, Vanaelst B, Molnar D, Bel-Serrat S, Mouratidou T, Moreno LA, Pala V, Eha M, Kourides YA, Siani A, Eiben G, Pigeot I (2013) Diet-obesity associations in children: approaches to counteract attenuation caused by misreporting. Public Health Nutr 16:256–266. (On behalf of the IDEFICS consortium)

    Article  PubMed  Google Scholar 

  8. Jenab M, Slimani N, Bictash M, Ferrari P, Bingham SA (2009) Biomarkers in nutritional epidemiology: applications, needs and new horizons. Hum Genet 125:507–525

    Article  PubMed  Google Scholar 

  9. Huybrechts I, Börnhorst C, Pala V, Moreno L, Barba G, Lissner L, Fraterman A, Veidebaum T, Hebestreit A, Sieri S, Ottevaere C, Tornaritis M, Molnár D, Ahrens W, De Henauw S, on behalf of the IDEFICS consortium (2011) Evaluation of the Children’s Eating Habits Questionnaire used in the IDEFICS study by relating urinary calcium and potassium to milk consumption frequencies among European children. Int J Obesity 35:S69–S78

    Article  CAS  Google Scholar 

  10. Börnhorst C, Bel-Serrat S, Pigeot I, Huybrechts I, Ottavaere C, Sioen I, De Henauw S, Mouratidou T, Mesana MI, Westerterp K, Bammann K, Lissner L, Eiben G, Pala V, Rayson M, Krogh V, Moreno LA (2014) Validity of 24-h recalls in (pre-)school aged children: comparison of proxy-reported energy intakes with measured energy expenditure. Clin Nutr 33:79–84. (On behalf of the IDEFICS consortium)

    Article  PubMed  Google Scholar 

  11. Menzies I (1972) Urinary excretion of sugars related to oral administration of disaccharides in adult coeliac disease. Clin Sci 42:18P

    Article  CAS  PubMed  Google Scholar 

  12. Nakamura H, Tamura Z (1972) Gas chromatographic analysis of mono-and disaccharides in human blood and urine after oral administration of disaccharides. Clin Chim Acta 39:367–381

    Article  CAS  PubMed  Google Scholar 

  13. Menzies IS (1974) Absorption of intact oligosaccharide in health and disease. Biochem Soc Trans 2:1042–1047

    Article  CAS  Google Scholar 

  14. Tasevska N, Runswick SA, McTaggart A, Bingham SA (2005) Urinary sucrose and fructose as biomarkers for sugar consumption. Cancer Epidemiol Biomark Prev 14:1287–1294

    Article  CAS  Google Scholar 

  15. Tasevska N, Runswick S, Welch A, McTaggart A, Bingham S (2009) Urinary sugars biomarker relates better to extrinsic than to intrinsic sugars intake in a metabolic study with volunteers consuming their normal diet. Eur J Clin Nutr 63:653–659

    Article  CAS  PubMed  Google Scholar 

  16. Tasevska N, Midthune D, Potischman N, Subar AF, Cross AJ, Bingham SA, Schatzkin A, Kipnis V (2011) Use of the predictive sugars biomarker to evaluate self-reported total sugars intake in the observing protein and energy nutrition (OPEN) study. Cancer Epidemiol Biomark Prev 20:490–500

    Article  CAS  Google Scholar 

  17. Luceri C, Caderni G, Lodovici M, Spagnesi MT, Monserrat C, Lancioni L, Dolara P (1996) Urinary excretion of sucrose and fructose as a predictor of sucrose intake in dietary intervention studies. Cancer Epidemiol Biomark Prev 5:167–171

    CAS  Google Scholar 

  18. Bingham S, Luben R, Welch A, Tasevska N, Wareham N, Khaw KT (2007) Epidemiologic assessment of sugars consumption using biomarkers: comparisons of obese and nonobese individuals in the European prospective investigation of cancer Norfolk. Cancer Epidemiol Biomark Prev 16:1651–1654

    Article  CAS  Google Scholar 

  19. Ahrens W, Bammann K, Siani A, Buchecker K, De Henauw S, Iacoviello L, Hebestreit A, Krogh V, Lissner L, Mårild S, Molnar D, Pitsiladis Y, Reisch L, Tornaritis M, Veidebaum T, Pigeot I, on behalf of the IDEFICS consortium (2011) The IDEFICS cohort: design, characteristics and participation in the baseline survey. Int J Obesity 35(Suppl 1):S3–S15

    Article  Google Scholar 

  20. Ahrens W, Siani A, Adan R, De Henauw S, Eiben G, Gwozdz W, Hebestreit A, Hunsberger M, Kaprio J, Krogh V, Lissner L, Molnar D, Moreno LA, Page A, Pico C, Reisch L, Smith RM, Tornaritis M, Veidebaum T, Williams G, Pohlabeln H, Pigeot I, On behalf of the I.Family consortium (2017) Cohort profile: the transition from childhood to adolescence in European children-how I.Family extends the IDEFICS cohort. Int J Epidemiol 46:1394–1395j

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Stomfai S, Ahrens W, Bammann K, Kovacs E, Mårild S, Michels N, Moreno L, Pohlabeln H, Siani A, Tornaritis M, on behalf of the IDEFICS consortium (2011) Intra-and inter-observer reliability in anthropometric measurements in children. Int J Obesity 35(Suppl 1):S45-S51

    Google Scholar 

  22. Suling M, Hebestreit A, Peplies J, Bammann K, Nappo A, Eiben G, Alvira JF, Verbestel V, Kovács E, Pitsiladis Y, Veidebaum T, Hadjigeorgiou C, Knof K, Ahrens W, on behalf of the IDEFICS consortium (2011) Design and results of the pretest of the IDEFICS study. Int J Obesity 35(Suppl 1):S30-S44

    Google Scholar 

  23. Cole T, Lobstein T (2012) Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatr Obes 7:284–294

    Article  CAS  PubMed  Google Scholar 

  24. Hebestreit A, Börnhorst C, Pala V, Barba G, Eiben G, Veidebaum T, Hadjigergiou C, Molnár D, Claessens M, Fernández-Alvira J, Pigeot I, on behalf of the IDEFICS consortium (2014) Dietary energy density in young children across Europe. Int J Obesity 38(Suppl 1):S124–S134

    Article  Google Scholar 

  25. Börnhorst C, Huybrechts I, Hebestreit A, Krogh V, De Decker A, Barba G, Moreno L, Lissner L, Tornaritis M, Loit H, Molnár D, Pigeot I, on behalf of the IDEFICS consortium (2014) Usual energy and macronutrient intakes in 2–9-year-old European children. Int J Obesity 38(Suppl 1):S115–S123

    Article  Google Scholar 

  26. Lanfer A, Knof K, Barba G, Veidebaum T, Papoutsou S, de Henauw S, Soos T, Moreno LA, Ahrens W, Lissner L, on behalf of the IDEFICS consortium (2012) Taste preferences in association with dietary habits and weight status in European children: results from the IDEFICS study. Int J Obesity 36:27–34

    Article  CAS  Google Scholar 

  27. Lissner L, Lanfer A, Gwozdz W, Olafsdottir S, Eiben G, Moreno LA, Santaliestra-Pasías AM, Kovács É, Barba G, Loit H-M, Kourides Y, Pala V, Pohlabeln H, De Henauw S, Buchecker K, Ahrens W, Reisch L (2012) Television habits in relation to overweight, diet and taste preferences in European children: the IDEFICS study. Eur J Epidemiol 27:705–715

    Article  PubMed  PubMed Central  Google Scholar 

  28. Dodd KW, Guenther PM, Freedman LS, Subar AF, Kipnis V, Midthune D, Tooze JA, Krebs-Smith SM (2006) Statistical methods for estimating usual intake of nutrients and foods: a review of the theory. J Am Diet Assoc 106:1640–1650

    Article  PubMed  Google Scholar 

  29. Tooze JA, Midthune D, Dodd KW, Freedman LS, Krebs-Smith SM, Subar AF, Guenther PM, Carroll RJ, Kipnis V (2006) A new statistical method for estimating the usual intake of episodically consumed foods with application to their distribution. J Am Diet Assoc 106:1575–1587

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kipnis V, Midthune D, Buckman DW, Dodd KW, Guenther PM, Krebs-Smith SM, Subar AF, Tooze JA, Carroll RJ, Freedman LS (2009) Modeling data with excess zeros and measurement error: application to evaluating relationships between episodically consumed foods and health outcomes. Biometrics 65:1003–1010

    Article  PubMed  PubMed Central  Google Scholar 

  31. Börnhorst C, Huybrechts I, Ahrens W, Eiben G, Michels N, Pala V, Molnar D, Russo P, Barba G, Bel-Serrat S, Moreno LA, Papoutsou S, Veidebaum T, Loit HM, Lissner L, Pigeot I, on behalf of the IDEFICS consortium (2013) Prevalence and determinants of misreporting among European children in proxy-reported 24 h dietary recalls. Br J Nutr 109:1257–1265

    Article  CAS  PubMed  Google Scholar 

  32. Bergmeyer HU (1974) Methods of enzymatic analysis, 2nd edn. Academic Press, New York

    Google Scholar 

  33. Kaaks R (1997) Biochemical markers as additional measurements in studies of the accuracy of dietary questionnaire measurements: conceptual issues. Am J Clin Nutr 65:1232S-1239S

    Article  PubMed  Google Scholar 

  34. R Core Team (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna

    Google Scholar 

  35. Johner SA, Libuda L, Shi L, Retzlaff A, Joslowski G, Remer T (2010) Urinary fructose: a potential biomarker for dietary fructose intake in children. Eur J Clin Nutr 64:1365–1370

    Article  CAS  PubMed  Google Scholar 

  36. Tasevska N, Midthune D, Tinker LF, Potischman N, Lampe JW, Neuhouser ML, Beasley JM, Van Horn L, Prentice RL, Kipnis V (2014) Use of a urinary sugars biomarker to assess measurement error in self-reported sugars intake in the nutrition and physical activity assessment study (NPAAS). Cancer Epidemiol Biomark Prev 23:2874–2883

    Article  CAS  Google Scholar 

  37. Assadi FK (2002) Quantitation of microalbuminuria using random urine samples. Pediatr Nephrol 17:107–110

    Article  PubMed  Google Scholar 

  38. Khaw K-T, Bingham S, Welch A, Luben R, O’Brien E, Wareham N, Day N (2004) Blood pressure and urinary sodium in men and women: the Norfolk Cohort of the European Prospective Investigation into Cancer (EPIC-Norfolk). Am J Clin Nutr 80:1397–1403

    Article  CAS  PubMed  Google Scholar 

  39. Campbell R, Tasevska N, Jackson KG, Sagi-Kiss V, di Paolo N, Mindell JS, Lister SJ, Khaw KT, Kuhnle GGC (2017) Association between urinary biomarkers of total sugars intake and measures of obesity in a cross-sectional study. PLoS One 12:e0179508

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was done as part of the I.Family Study (http://www.ifamilystudy.eu/). We gratefully acknowledge the financial support of the European Commission within the Seventh RTD Framework Programme Contract No. 266044. We thank the I.Family children and their parents for participating in this extensive examination. We are grateful for the support from school boards, headmasters and communities.

Author information

Authors and Affiliations

Authors

Consortia

Corresponding author

Correspondence to Timm Intemann.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethical standards

We certify that all applicable institutional and governmental regulations concerning the ethical use of human volunteers were followed during this research. The study was approved by the local ethics committee in each center and has been conducted according to the guidelines laid down in the 1964 Declaration of Helsinki and its later amendments. Study participants did not undergo any procedures unless they (and their parents) had given consent for examinations, collection of samples, subsequent analysis and storage of personal data and collected samples. Study subjects and their parents could consent to single components of the study while abstaining from others.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 26 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Intemann, T., Pigeot, I., De Henauw, S. et al. Urinary sucrose and fructose to validate self-reported sugar intake in children and adolescents: results from the I.Family study. Eur J Nutr 58, 1247–1258 (2019). https://doi.org/10.1007/s00394-018-1649-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00394-018-1649-6

Keywords

Navigation