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

Development of the food-based Lifelines Diet Score (LLDS) and its application in 129,369 Lifelines participants

European Journal of Clinical Nutrition volume 72, pages 1111–1119 (2018)Cite this article

Subjects

A Correction to this article was published on 24 June 2019

This article has been updated

Abstract

Background/objectives

Many diet quality scores exist, but fully food-based scores based on contemporary evidence are scarce. Our aim was to develop a food-based diet score based on international literature and examine its discriminative capacity and socio-demographic determinants.

Subjects/methods

Between 2006 and 2013, dietary intake of 129,369 participants of the Lifelines Cohort (42% male, 45 ± 13 years (range 18–93)) was assessed with a 110-item food frequency questionnaire. Based on the 2015 Dutch Dietary Guidelines and underlying literature, nine food groups with positive (vegetables, fruit, whole grain products, legumes&nuts, fish, oils&soft margarines, unsweetened dairy, coffee and tea) and three food groups with negative health effects (red&processed meat, butter&hard margarines and sugar-sweetened beverages) were identified. Per food group, the intake in grams per 1000 kcal was categorized into quintiles, awarded 0 to 4 points (negative groups scored inversely) and summed. Food groups with neutral, unknown or inconclusive evidence are described but not included.

Results

The Lifelines Diet Score (LLDS) discriminated well between high and low consumers of included food groups. This is illustrated by e.g. a 2-fold higher vegetable intake in the highest, compared to the lowest LLDS quintile. Differences were 5.5-fold for fruit, 3.5-fold for fish, 3-fold for dairy and 8-fold for sugar-sweetened beverages. The LLDS was higher in females and positively associated with age and educational level.

Conclusions

The LLDS is based on the latest international evidence for diet-disease relations at the food group level and has high capacity to discriminate people with widely different intakes. Together with the population-based quintile approach, this makes the LLDS a flexible, widely applicable tool for diet quality assessment.

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

Fig. 1
Fig. 2

Similar content being viewed by others

Change history

  • 24 June 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Kromhout D, Spaaij CJK, de Goede J, Weggemans RM. The 2015 Dutch food-based dietary guidelines. Eur J Clin Nutr. 2016;70:869–78.

    Article  CAS  Google Scholar 

  2. Mozaffarian D, Ludwig DS. Dietary guidelines in the 21st century–a time for food. JAMA. 2010;304:681–2.

    Article  CAS  Google Scholar 

  3. Jacobs DR, Tapsell LC. Food synergy: the key to a healthy diet. Proc Nutr Soc. 2013;72:200–6.

    Article  Google Scholar 

  4. Food and Agriculture Organization of the United Nations. Background | Food-based dietary guidelines. http://www.fao.org/nutrition/education/food-dietary-guidelines/background/en/

  5. Kennedy ET, Ohls J, Carlson S, Fleming K. The healthy eating index: design and applications. J Am Diet Assoc. 1995;95:1103–8.

    Article  CAS  Google Scholar 

  6. Guenther PM, Casavale KO, Kirkpatrick SI, Reedy J, Hiza HAB, Kuczynski KJ, et al.Update of the healthy eating index: HEI-2010.J Acad Nutr Diet. 2013;113:1–20.

    Google Scholar 

  7. Trichopoulou A, Kouris-Blazos A, Wahlqvist ML, Gnardellis C, Lagiou P, Polychronopoulos E, et al. Diet and overall survival in elderly people. BMJ Br Med J. 1995;311:1457–60.

    Article  CAS  Google Scholar 

  8. Sofi F, Macchi C, Abbate R, Gensini GF, Casini A. Mediterranean diet and health status: An updated meta-analysis and a proposal for a literature-based adherence score. Public Health Nutr. 2014;17:2769–82.

    Article  Google Scholar 

  9. Onvani S. Haghighatdoost F, Surkan PJ, Larijani B, Azadbakht L. Adherence to the Healthy Eating Index and Alternative Healthy Eating Index dietary patterns and mortality from all causes, cardiovascular disease and cancer: a meta-analysis of observational studies. J Hum Nutr Diet. 2017;30:216–26.

    Article  CAS  Google Scholar 

  10. Knoops KTB, de Groot LCPGM, Kromhout D, Perrin A-E, Moreiras-Varela O, Menotti A, et al. Mediterranean diet, lifestyle factors, and 10-year mortality in elderly European men and women: the HALE project. JAMA. 2004;292:1433–9.

    Article  Google Scholar 

  11. Aune D, Lau R, Chan DSM, Vieira R, Greenwood DC, Kampman E, et al. Dairy products and colorectal cancer risk: a systematic review and meta-analysis of cohort studies. Ann Oncol. 2012;23:37–45.

    Article  CAS  Google Scholar 

  12. Chen M, Sun Q, Giovannucci E, Mozaffarian D, Manson JE, Willett WC, et al. Dairy consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. BMC Med. 2014;12:215.

    Article  Google Scholar 

  13. Malik VS, Pan A, Willett WC, Hu FB. Sugar-sweetened beverages and weight gain in children and adults: a systematic review and meta-analysis. Am J Clin Nutr. 2013;98:1084–102.

    Article  CAS  Google Scholar 

  14. Greenwood DC, Threapleton DE, Evans CEL, Cleghorn CL, Nykjaer C, Woodhead C, et al. Association between sugar-sweetened and artificially sweetened soft drinks and type 2 diabetes: systematic review and dose–response meta-analysis of prospective studies. Br J Nutr. 2014;112:725–34.

    Article  CAS  Google Scholar 

  15. Scholtens S, Smidt N, Swertz MA, Bakker SJL, Dotinga A, Vonk JM, et al. Cohort Profile: LifeLines, a three-generation cohort study and biobank. Int J Epidemiol. 2015;44:1172–80.

    Article  Google Scholar 

  16. Dekker LH, Rijnks RH, Strijker D, Navis GJ. A spatial analysis of dietary patterns in a large representative population in the north of The Netherlands—the Lifelines cohort study. Int J Behav Nutr Phys Act. 2017;14:166.

    Article  Google Scholar 

  17. Stolk RP, Rosmalen JGM, Postma DS, De Boer RA, Navis G, Slaets JPJ, et al. Universal risk factors for multifactorial diseases: LifeLines: A three-generation population-based study. Eur J Epidemiol. 2008;23:67–74.

    Article  Google Scholar 

  18. Black AE. Critical evaluation of energy intake using the Goldberg cut-off for energy intake: basal metabolic rate. A practical guide to its calculation, use and limitations. Int J Obes Relat Metab Disord. 2000;24:1119–30.

    Article  CAS  Google Scholar 

  19. Schofield WN. Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr. 1985;39(Suppl 1):5–41.

    PubMed  Google Scholar 

  20. Molag ML, de Vries JHM, Duif N, Ocké MC, Dagnelie PC, Goldbohm RA, et al. Selecting informative food items for compiling food-frequency questionnaires: comparison of procedures. Br J Nutr. 2010;104:446–56.

    Article  CAS  Google Scholar 

  21. NEVO-tabel. Dutch Food Composition Table 2011—version 3. 2011. http://www.rivm.nl/Documenten_en_publicaties/Algemeen_Actueel/Nieuwsberichten/2011/Nieuwe_NEVO_tabel_2011_beschikbaar

  22. Meyer KA, Sijtsma FPC, Nettleton JA, Steffen LM, Horn LVan, Shikany JM, et al. Dietary patterns are associated with plasma F2-isoprostanes in an observational cohort study of adults. Free Radic Biol Med. 2013;57:201–9.

    Article  CAS  Google Scholar 

  23. Sijtsma FPC, Meyer KA, Steffen LM, Van Horn L, Shikany JM, Odegaard AO, et al. Diet quality and markers of endothelial function: The CARDIA study. Nutr Metab Cardiovasc Dis. 2014;24:632–8.

    Article  CAS  Google Scholar 

  24. Jacobs DR, Orlich MJ. Diet pattern and longevity: Do simple rules suffice? A commentary. Am J Clin Nutr. 2014;100:313S–9S. (suppl)

    Article  CAS  Google Scholar 

  25. Faber J, Fonseca LM. How sample size influences research outcomes. Dent Press J Orthod. 2014;19:27–9.

    Article  Google Scholar 

  26. Dutch National Food Consumption Survey 2007–2010, Part 1 Food groups. 2010. p. 1–383. http://www.rivm.nl/Documenten_en_publicaties/Wetenschappelijk/Tabellen_grafieken/Leefstijl_Voeding/VCP/Basis_2011/VCP_2007_2010_Deel_1_Voedingsmiddelen_EPIC_Soft_groepen/Download/VCP_2007_2010_Deel_1_Voedingsmiddelen_EPIC_Soft_groepen.org

  27. Buscemi S, Rosafio G, Vasto S, Massenti FM, Grosso G, Galvano F, et al. Validation of a food frequency questionnaire for use in Italian adults living in Sicily. Int J Food Sci Nutr. 2015;66:426–38.

    Article  Google Scholar 

  28. Svensson Å, Renström F, Bluck L, Lissner L, Franks PW, Larsson C. Dietary intake assessment in women with different weight and pregnancy status using a short questionnaire. Public Health Nutr. 2014;17:1939–48.

    Article  Google Scholar 

  29. Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003;348:2599–608.

    Article  Google Scholar 

  30. Wang DD, Leung CW, Li Y, Ding EL, Chiuve SE, Hu FB, et al. Trends in dietary quality among adults in the United States, 1999 through 2010. JAMA Intern Med. 2014;174:1587–95.

    Article  Google Scholar 

  31. Mursu J, Steffen LM, Meyer KA, Duprez D, Jacobs DR Jr. Diet quality indexes and mortality in postmenopausal women: the Iowa Women’s Health Study. Am J Clin Nutr. 2013;98:444–53.

    Article  CAS  Google Scholar 

  32. Sijtsma FPC, Meyer KA, Steffen LM, Shikany JM, Van Horn L, Harnack L, et al. Longitudinal trends in diet and effects of sex, race, and education on dietary quality score change: The Coronary Artery Risk Development in Young Adults study. Am J Clin Nutr. 2012;95:580–6.

    Article  CAS  Google Scholar 

  33. Hu EA, Toledo E, Diez-Espino J, Estruch R, Corella D, Salas-Salvado J, et al. Lifestyles and risk factors associated with adherence to the Mediterranean diet: a baseline assessment of the PREDIMED trial. PLoS ONE. 2013;8:e60166.

    Article  CAS  Google Scholar 

  34. Guenther PM, Kirkpatrick SI, Reedy J, Krebs-Smith SM, Buckman DW, Dodd KW, et al. The Healthy Eating Index-2010 Is a Valid and Reliable Measure of Diet Quality According to the 2010 Dietary Guidelines for Americans. J Nutr. 2014;144:399–407.

    Article  CAS  Google Scholar 

  35. Cai L, Ma D, Zhang Y, Liu Z, Wang P. The effect of coffee consumption on serum lipids: a meta-analysis of randomized controlled trials. Eur J Clin Nutr. 2012;66:872–7.

    Article  CAS  Google Scholar 

  36. Ding M, Bhupathiraju SN, Chen M, van Dam RM, Hu FB. Caffeinated and decaffeinated coffee consumption and risk of type 2 diabetes: a systematic review and a dose-response meta-analysis. Diabetes Care. 2014;37:569–86.

    Article  Google Scholar 

  37. Ding M, Bhupathiraju SN, Satija A, van Dam RM, Hu FB, et al. Long-term coffee consumption and risk of cardiovascular disease: a systematic review and a dose-response meta-analysis of prospective cohort studies. Circulation. 2014;129:643–59.

    Article  CAS  Google Scholar 

  38. Afshin A, Micha R, Khatibzadeh S, Mozaffarian D. Consumption of nuts and legumes and risk of incident ischemic heart disease, stroke, and diabetes: a systematic review and meta-analysis. Am J Clin Nutr. 2014;100:278–89.

    Article  CAS  Google Scholar 

  39. Ha V, Sievenpiper JL, de Souza RJ, Jayalath VH, Mirrahimi A, Agarwal A, et al. Effect of dietary pulse intake on established therapeutic review and meta-analysis of randomized controlled trials. Can Med Assoc J. 2014;186:252–62.

    Article  Google Scholar 

  40. Sabaté J, Oda K, Ros E. Nut consumption and blood lipid levels. JAMA Intern Med. 2014;170:821–7.

    Article  Google Scholar 

  41. Dutch National Food Consumption Survey 2007–2010, Part 2 Total Foods. 2010. pp. 1157–3368. http://www.rivm.nl/Documenten_en_publicaties/Wetenschappelijk/Tabellen_grafieken/Leefstijl_Voeding/VCP/Basis_2011/VCP_2007_2010_Deel_2_Voedingsmiddelen_NEVO_codes/Download/VCP_2007_2010_Deel_2_Voedingsmiddelen_NEVO_codes.org

Download references

Acknowledgements

The Lifelines Biobank initiative has been made possible by funds from FES (Fonds Economische Structuurversterking), SNN (Samenwerkingsverband Noord Nederland), and REP (Ruimtelijk Economisch Programma). We acknowledge the services of the Lifelines Cohort Study, the contributing research centers delivering data to Lifelines, and all study participants.

Funding

This study was partly funded by the Nutrition & Health initiative of the University of Groningen.

Author information

Authors and Affiliations

  1. Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

    Petra C. Vinke, Eva Corpeleijn & Daan Kromhout

  2. Department of Nephrology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands

    Louise H. Dekker & Gerjan Navis

  3. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA

    David R. Jacobs Jr

Authors
  1. Petra C. Vinke
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eva Corpeleijn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Louise H. Dekker
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. David R. Jacobs Jr
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gerjan Navis
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Daan Kromhout
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Petra C. Vinke.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vinke, P.C., Corpeleijn, E., Dekker, L.H. et al. Development of the food-based Lifelines Diet Score (LLDS) and its application in 129,369 Lifelines participants. Eur J Clin Nutr 72, 1111–1119 (2018). https://doi.org/10.1038/s41430-018-0205-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41430-018-0205-z

This article is cited by

Search

Advanced search

Quick links