Individual characteristics associated with changes in the contribution of plant foods to dietary intake in a French prospective cohort

  • Zoé ColombetEmail author
  • Benjamin Allès
  • Wendy Si Hassen
  • Aurélie Lampuré
  • Emmanuelle Kesse-Guyot
  • Sandrine Péneau
  • Serge Hercberg
  • Caroline Méjean
Original Contribution



Rebalancing the contribution of animal- and plant-based foods is needed to achieve sustainable diet. However, little is known concerning individual characteristics that may influence intake of plant-based foods and their changes over time. We aimed to assess changes in the contribution of plant-based foods to dietary intake over time and their association with individual characteristics.


The contribution of plant-based foods was assessed by percent energy intake provided by plant proteins in diet (PEIPP) and a score of adherence to a pro-vegetarian diet, using repeated 24-h records in 15,615 French adults participating in the NutriNet-Santé cohort study. Associations between baseline individual characteristics and changes in the two indicators over a 4–6-year follow-up were assessed using a linear mixed model.


At baseline, PEIPP and pro-vegetarian score were positively associated with age [β65+ = 0.80, 95% CI = (0.71, 0.88), β65+ = 3.30, 95% CI = (2.97, 3.64), respectively] and education [βpostgraduate = 0.23, 95% CI = (0.12, 0.34), βpostgraduate = 1.19, 95% CI = (0.75, 1.62)], while they were inversely associated with BMI class [βobesity = − 0.48, 95% CI = (0.56, 0.41), βobesity = − 2.31, 95% CI = (− 2.63, − 1.98)]. Men had higher PEIPP than women [β = 0.06, 95% CI = (0.01, 0.11)]. Pro-vegetarian score significantly increased over time [β = 0.23, 95% CI = (0.08, 0.37)]. The older the individual at baseline, the greater the decrease in the two indicators during follow-up. Pro-vegetarian score increased during follow-up for obese participants at baseline.


The contribution of plant-based foods was associated with several socio-demographic and economic characteristics at baseline, whereas change over time was related to age and weight status. Further analysis of individual obstacles and lever to consume plant-based foods is needed.


Plant-based foods Plant proteins Dietary change Sustainable diet Longitudinal analysis Individual characteristics 


95% CI

95% Confidence Interval


Analysis of Variance


Body Mass Index


Basal Metabolic Rate


Coronary Artery Risk Development in Young Adults


Etude Nationale Nutrition Santé


Individual and National Consumption Survey 2


Percent Energy Intake Provided by Plant Proteins


Standard Deviation


Standard Error


Urban Unit


World Health Organization


Compliance with ethical standards

Conflict of interest

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

Supplementary material

394_2018_1752_MOESM1_ESM.docx (55 kb)
Supplementary material 1 (DOCX 55 KB)


  1. 1.
    Burlingame B, Dernini, Nutrition and Consumer Protection Division, Food and Agriculture Organization of the United Nations (FAO) (2012) Sustainable diets and biodiversity—directions and solutions for policy research and action. FAO, RomeGoogle Scholar
  2. 2.
    Carlsson-Kanyama A, González AD (2009) Potential contributions of food consumption patterns to climate change. Am J Clin Nutr 89:1704S–1709S. CrossRefPubMedGoogle Scholar
  3. 3.
    McMichael AJ, Powles JW, Butler CD, Uauy R (2007) Food, livestock production, energy, climate change, and health. Lancet Lond Engl 370:1253–1263. CrossRefGoogle Scholar
  4. 4.
    World Cancer Research Fund, American Institute for Cancer Research (2007) Food, nutrition, physical activity and the prevention of cancer: a global perspective. American Institute for Cancer Research, Washington, D.CGoogle Scholar
  5. 5.
    Micha R, Wallace SK, Mozaffarian D (2010) Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis. Circulation 121:2271–2283. CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Sinha R, Cross AJ, Graubard BI et al (2009) Meat intake and mortality: a prospective study of over half a million people. Arch Intern Med 169:562–571. CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Pan A, Sun Q, Bernstein AM et al (2012) Red meat consumption and mortality: results from 2 prospective cohort studies. Arch Intern Med 172:555–563. CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Nagao M, Iso H, Yamagishi K et al (2012) Meat consumption in relation to mortality from cardiovascular disease among Japanese men and women. Eur J Clin Nutr 66:687–693. CrossRefPubMedGoogle Scholar
  9. 9.
    Huang T, Yang B, Zheng J et al (2012) Cardiovascular disease mortality and cancer incidence in vegetarians: a meta-analysis and systematic review. Ann Nutr Metab 60:233–240. CrossRefPubMedGoogle Scholar
  10. 10.
    Aston LM, Smith JN, Powles JW (2012) Impact of a reduced red and processed meat dietary pattern on disease risks and greenhouse gas emissions in the UK: a modelling study. BMJ Open. CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Scarborough P, Allender S, Clarke D et al (2012) Modelling the health impact of environmentally sustainable dietary scenarios in the UK. Eur J Clin Nutr 66:710–715. CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Key TJ, Appleby PN, Crowe FL et al (2014) Cancer in British vegetarians: updated analyses of 4998 incident cancers in a cohort of 32,491 meat eaters, 8612 fish eaters, 18,298 vegetarians, and 2246 vegans. Am J Clin Nutr 100(Suppl 1):378S–385S. CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Chang-Claude J, Hermann S, Eilber U, Steindorf K (2005) Lifestyle determinants and mortality in German vegetarians and health-conscious persons: results of a 21-year follow-up. Cancer Epidemiol Biomark Prev Publ Am Assoc Cancer Res Cospons Am Soc Prev Oncol 14:963–968. CrossRefGoogle Scholar
  14. 14.
    Key TJ, Appleby PN, Spencer EA et al (2009) Mortality in British vegetarians: results from the European Prospective Investigation into Cancer and Nutrition (EPIC-Oxford). Am J Clin Nutr 89:1613S–1619S. CrossRefPubMedGoogle Scholar
  15. 15.
    Pimentel D, Pimentel M (2003) Sustainability of meat-based and plant-based diets and the environment. Am J Clin Nutr 78:660S–663SCrossRefPubMedGoogle Scholar
  16. 16.
    Darmon N, Drewnowski A (2008) Does social class predict diet quality? Am J Clin Nutr 87:1107–1117CrossRefPubMedGoogle Scholar
  17. 17.
    Micha R, Khatibzadeh S, Shi P et al (2015) Global, regional and national consumption of major food groups in 1990 and 2010: a systematic analysis including 266 country-specific nutrition surveys worldwide. BMJ Open 5:e008705. CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Drewnowski A, Shultz JM (2001) Impact of aging on eating behaviors, food choices, nutrition, and health status. J Nutr Health Aging 5:75–79PubMedGoogle Scholar
  19. 19.
    Laforge RG, Greene GW, Prochaska JO (1994) Psychosocial factors influencing low fruit and vegetable consumption. J Behav Med 17:361–374CrossRefPubMedGoogle Scholar
  20. 20.
    Devine CM, Wolfe WS, Frongillo EA, Bisogni CA (1999) Life-course events and experiences: association with fruit and vegetable consumption in 3 ethnic groups. J Am Diet Assoc 99:309–314. CrossRefPubMedGoogle Scholar
  21. 21.
    Lea EJ, Crawford D, Worsley A (2006) Consumers’ readiness to eat a plant-based diet. Eur J Clin Nutr 60:342–351. CrossRefPubMedGoogle Scholar
  22. 22.
    Sijtsma FPC, Meyer KA, Steffen LM et al (2012) 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 95:580–586. CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Arabshahi S, Lahmann PH, Williams GM et al (2011) Longitudinal change in diet quality in Australian adults varies by demographic, socio-economic, and lifestyle characteristics. J Nutr 141:1871–1879. CrossRefPubMedGoogle Scholar
  24. 24.
    Roos E, Talala K, Laaksonen M et al (2008) Trends of socioeconomic differences in daily vegetable consumption, 1979–2002. Eur J Clin Nutr 62:823–833. CrossRefPubMedGoogle Scholar
  25. 25.
    Harrington JM, Dahly DL, Fitzgerald AP et al (2014) Capturing changes in dietary patterns among older adults: a latent class analysis of an ageing Irish cohort. Public Health Nutr 17:2674–2686. CrossRefPubMedGoogle Scholar
  26. 26.
    Eng PM, Kawachi I, Fitzmaurice G, Rimm EB (2005) Effects of marital transitions on changes in dietary and other health behaviours in US male health professionals. J Epidemiol Community Health 59:56–62. CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Lee S, Cho E, Grodstein F et al (2005) Effects of marital transitions on changes in dietary and other health behaviours in US women. Int J Epidemiol 34:69–78. CrossRefPubMedGoogle Scholar
  28. 28.
    Vinther JL, Conklin AI, Wareham NJ, Monsivais P (2016) Marital transitions and associated changes in fruit and vegetable intake: findings from the population-based prospective EPIC-Norfolk cohort, UK. Soc Sci Med 1982 157:120–126. CrossRefGoogle Scholar
  29. 29.
    Vainio A, Niva M, Jallinoja P, Latvala T (2016) From beef to beans: eating motives and the replacement of animal proteins with plant proteins among Finnish consumers. Appetite 106:92–100. CrossRefPubMedGoogle Scholar
  30. 30.
    Martínez-González MA, Sánchez-Tainta A, Corella D et al (2014) A provegetarian food pattern and reduction in total mortality in the Prevención con Dieta Mediterránea (PREDIMED) study. Am J Clin Nutr 100(Suppl 1):320S–320S8S. CrossRefPubMedGoogle Scholar
  31. 31.
    Lin Y, Bolca S, Vandevijvere S et al (2011) Plant and animal protein intake and its association with overweight and obesity among the Belgian population. Br J Nutr 105:1106–1116. CrossRefPubMedGoogle Scholar
  32. 32.
    Camilleri GM, Verger EO, Huneau J-F et al (2013) Plant and animal protein intakes are differently associated with nutrient adequacy of the diet of French adults. J Nutr 143:1466–1473. CrossRefPubMedGoogle Scholar
  33. 33.
    Lin Y, Bolca S, Vandevijvere S et al (2011) Dietary sources of animal and plant protein intake among Flemish preschool children and the association with socio-economic and lifestyle-related factors. Nutr J 10:97. CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Halkjaer J, Olsen A, Bjerregaard LJ et al (2009) Intake of total, animal and plant proteins, and their food sources in 10 countries in the European Prospective Investigation into Cancer and Nutrition. Eur J Clin Nutr 63(Suppl 4):S16–S36. CrossRefPubMedGoogle Scholar
  35. 35.
    Hercberg S, Castetbon K, Czernichow S et al (2010) The Nutrinet-Santé Study: a web-based prospective study on the relationship between nutrition and health and determinants of dietary patterns and nutritional status. BMC Public Health 10:242. CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Touvier M, Kesse-Guyot E, Méjean C et al (2011) Comparison between an interactive web-based self-administered 24 h dietary record and an interview by a dietitian for large-scale epidemiological studies. Br J Nutr 105:1055–1064. CrossRefPubMedGoogle Scholar
  37. 37.
    Lassale C, Castetbon K, Laporte F et al (2015) Validation of a Web-based, self-administered, non-consecutive-day dietary record tool against urinary biomarkers. Br J Nutr 113:953–962. CrossRefPubMedGoogle Scholar
  38. 38.
    Lassale C, Castetbon K, Laporte F et al (2016) Correlations between fruit, vegetables, fish, vitamins, and fatty acids estimated by web-based nonconsecutive dietary records and respective biomarkers of nutritional status. J Acad Nutr Diet 116:427–438.e5. CrossRefPubMedGoogle Scholar
  39. 39.
    Le Moullec N, Deheeger M, Preziosi P et al (1996) Validation du manuel-photos utilisé pour l’enquête alimentaire de l’étude SU.VI.MAX. Cah Nutr Diététique 31:158–164Google Scholar
  40. 40.
    Arnault N, Caillot L, Castetbon K et al (2013) Table de Composition des aliments NutriNet-Santé. Edition Économica, ParisGoogle Scholar
  41. 41.
    Bianchi CM, Egnell M, Huneau J-F, Mariotti F (2016) Plant protein intake and dietary diversity are independently associated with nutrient adequacy in French adults. J Nutr 146:2351–2360. CrossRefPubMedGoogle Scholar
  42. 42.
    Willett W (1998) Nutritional epidemiology. Oxford University Press, OxfordCrossRefGoogle Scholar
  43. 43.
    World Health Organization (WHO) Expert Committee (1995) Physical status: the use and interpretation of anthropometry. Report of a WHO Expert Committee. World Health Organ Tech Rep Ser 854:1–452Google Scholar
  44. 44.
    Lassale C, Péneau S, Touvier M et al (2013) Validity of web-based self-reported weight and height: results of the Nutrinet-Santé study. J Med Internet Res 15:e152. CrossRefPubMedPubMedCentralGoogle Scholar
  45. 45.
    Black AE (2000) 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 J Int Assoc Study Obes 24:1119–1130CrossRefGoogle Scholar
  46. 46.
    Schofield WN (1985) Predicting basal metabolic rate, new standards and review of previous work. Hum Nutr Clin Nutr 39(Suppl 1):5–41PubMedGoogle Scholar
  47. 47.
    Institut national de la statistique et des études économiques (Insee) La macro SAS CALMAR. Accessed 20 Mar 2016
  48. 48.
    Laird NM, Ware JH (1982) Random-effects models for longitudinal data. Biometrics 38:963–974CrossRefPubMedGoogle Scholar
  49. 49.
    FranceAgriMer (2011) Crise économique et comportements de consommation alimentaire des Français. Les cahiers de FranceAgriMer Les étudesGoogle Scholar
  50. 50.
    FranceAgriMer (2015) Impact de la crise économique sur la consommation de viandes et évolutions des comportements alimentaires. Les synthèses de FranceAgriMer Élevage/Viandes 21Google Scholar
  51. 51.
    O’Doherty Jensen K, Holm L (1999) Preferences, quantities and concerns: socio-cultural perspectives on the gendered consumption of foods. Eur J Clin Nutr 53:351–359CrossRefPubMedGoogle Scholar
  52. 52.
    Kimura Y, Ogawa H, Yoshihara A et al (2013) Evaluation of chewing ability and its relationship with activities of daily living, depression, cognitive status and food intake in the community-dwelling elderly. Geriatr Gerontol Int 13:718–725. CrossRefPubMedGoogle Scholar
  53. 53.
    Galobardes B, Shaw M, Lawlor DA et al (2006) Indicators of socioeconomic position (part 1). J Epidemiol Community Health 60:7–12. CrossRefPubMedPubMedCentralGoogle Scholar
  54. 54.
    Méjean C, Si Hassen W, Lecossais C et al (2016) Socio-economic indicators are independently associated with intake of animal foods in French adults. Public Health Nutr 19:3146–3157. CrossRefPubMedGoogle Scholar
  55. 55.
    Touvier M, Kesse-Guyot E, Méjean C et al (2010) Variations in compliance with recommendations and types of meat/seafood/eggs according to sociodemographic and socioeconomic categories. Ann Nutr Metab 56:65–73. CrossRefPubMedGoogle Scholar
  56. 56.
    Hercberg S, Chat-Yung S, Chaulia M (2008) The French National Nutrition and Health Program: 2001–2006–2010. Int J Public Health 53:68–77CrossRefPubMedGoogle Scholar
  57. 57.
    Schäfer M, Herde A, Kropp C, others (2010) Life events as turning points for sustainable nutrition. Syst Innov Sustain 4:210–226Google Scholar
  58. 58.
    Bujnowski D, Xun P, Daviglus ML et al (2011) Longitudinal association between animal and vegetable protein intake and obesity among adult males in the United States: the Chicago Western Electric Study. J Am Diet Assoc 111:1150–1155.e1. CrossRefPubMedPubMedCentralGoogle Scholar
  59. 59.
    Andreeva VA, Salanave B, Castetbon K et al (2015) Comparison of the sociodemographic characteristics of the large NutriNet-Santé e-cohort with French Census data: the issue of volunteer bias revisited. J Epidemiol Community Health 69:893–898. CrossRefPubMedGoogle Scholar
  60. 60.
    Andreeva VA, Deschamps V, Salanave B et al (2016) Comparison of Dietary Intakes Between a Large Online Cohort Study (Etude NutriNet-Santé) and a Nationally Representative Cross-Sectional Study (Etude Nationale Nutrition Santé) in France: addressing the issue of generalizability in E-epidemiology. Am J Epidemiol 184:660–669. CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Wethington E (2005) An overview of the life course perspective: implications for health and nutrition. J Nutr Educ Behav 37:115–120CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Zoé Colombet
    • 1
    • 4
    Email author return OK on get
  • Benjamin Allès
    • 1
  • Wendy Si Hassen
    • 1
  • Aurélie Lampuré
    • 1
  • Emmanuelle Kesse-Guyot
    • 1
  • Sandrine Péneau
    • 1
  • Serge Hercberg
    • 1
    • 2
  • Caroline Méjean
    • 3
  1. 1.Université Paris 13, Sorbonne Paris Cité, Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre d’Epidémiologie et Statistiques Paris Nord, Inserm (U1153), Inra (U1125), CnamBobignyFrance
  2. 2.Department of Public HealthHôpital AvicenneBobignyFrance
  3. 3.MOISA, Univ Montpellier, CIRAD, CIHEAM-IAMM, INRA, Montpellier SupAgroMontpellierFrance
  4. 4.EREN, SMBH Paris 13Bobigny CedexFrance

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