European Journal of Nutrition

, Volume 57, Issue 7, pp 2477–2488 | Cite as

Association between organic food consumption and metabolic syndrome: cross-sectional results from the NutriNet-Santé study

  • Julia BaudryEmail author
  • Hélène Lelong
  • Solia Adriouch
  • Chantal Julia
  • Benjamin Allès
  • Serge Hercberg
  • Mathilde Touvier
  • Denis Lairon
  • Pilar Galan
  • Emmanuelle Kesse-Guyot
Original Contribution



Metabolic syndrome (MetS), a multicomponent condition, is a cardiovascular disease predictor. Although exposure to agricultural pesticides has been suggested as a potential contributor to the rising rates of obesity, type 2 diabetes, and other features of metabolic disorders, no studies have focused on the association between consumption of organic food (produced without synthetic pesticides) and MetS. We aimed to investigate the cross-sectional association between organic food consumption and MetS in French adults to determine whether it would be worth conducting further studies, particularly large prospective and randomised trials.


A total of 8174 participants from the NutriNet-Santé study who attended a clinical visit and completed an organic food frequency questionnaire were included in this cross-sectional analysis. We evaluated the association between the proportion of organic food in the diet (overall and by food group) and MetS using Poisson regression models while adjusting for potential confounders.


Higher organic food consumption was negatively associated with the prevalence of MetS: adjusted prevalence ratio was 0.69 (95% CI 0.61, 0.78) when comparing the third tertile of proportion of organic food in the diet with the first one (p value <0.0001). Higher consumption of organic plant-based foods was also related to a lower probability of having MetS. In addition, when stratifying by lifestyle factors (nutritional quality of the diet, smoking status, and physical activity), a significant negative association was detected in each subgroup (p values <0.05), except among smokers.


Our results showed that a higher organic food consumption was associated with a lower probability of having MetS. Additional prospective studies and randomised trials are required to ascertain the relationship between organic food consumption and metabolic disorders.


Metabolic syndrome Metabolic traits Organic food consumption Dietary pattern 



Body mass index


Confidence intervals


National commission on informatics and liberty


Diastolic blood pressure


European food safety authority


French National Nutrition and Health Survey


High-density protein


Institutional Review Board of the French Institute for Health and Medical Research


French National Institute of Statistics and Economic Studies


International Physical Activity Questionnaire


Low-density protein


Metabolic syndrome


Modified Programme National Nutrition Guideline Score


Organic Food Frequency Questionnaire


Persistent organic pollutants


Polyunsaturated fatty acids


Prevalence ratios


Systolic blood pressure



We thank all the people who helped carry out the NutriNet-Santé study and all dedicated and conscientious volunteers. We especially thank Younes Esseddik, Paul Flanzy, Nathalie Arnault, Fabien Szabo, Laurent Bourhis, and Cédric Agaesse.

Author contributions

SH, PG, DL, and EKG conceived and designed research; JB performed the statistical analysis and wrote the article; JB, HL, SA, CJ, BA, SH, MT, DL, PG, and EKG were involved in revising the work critically for important intellectual content; and JB had primary responsibility for final content. All authors read and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

None of the authors declares any conflicts of interest.


The BioNutriNet project was supported by the French National Research Agency (Agence Nationale de la Recherche) in the context of the 2013 Programme de Recherche Systèmes Alimentaires Durables (ANR-13-ALID-0001). The NutriNet-Santé cohort study is funded by the following public institutions: Ministère de la Santé, Santé Publique France, Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Recherche Agronomique (INRA), Conservatoire National des Arts et Métiers (CNAM), and Paris 13 University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


  1. 1.
    Galassi A, Reynolds K, He J (2006) Metabolic syndrome and risk of cardiovascular disease: a meta-analysis. Am J Med 119:812–819. doi: 10.1016/j.amjmed.2006.02.031 CrossRefPubMedGoogle Scholar
  2. 2.
    Gami AS, Witt BJ, Howard DE et al (2007) Metabolic syndrome and risk of incident cardiovascular events and death. J Am Coll Cardiol 49:403–414. doi: 10.1016/j.jacc.2006.09.032 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Wang J, Ruotsalainen S, Moilanen L et al (2007) The metabolic syndrome predicts cardiovascular mortality: a 13-year follow-up study in elderly non-diabetic Finns. Eur Heart J 28:857–864. doi: 10.1093/eurheartj/ehl524 CrossRefPubMedGoogle Scholar
  4. 4.
    Benetos A, Thomas F, Pannier B et al (2008) All-cause and cardiovascular mortality using the different definitions of metabolic syndrome. Am J Cardiol 102:188–191. doi: 10.1016/j.amjcard.2008.03.037 CrossRefPubMedGoogle Scholar
  5. 5.
    Alberti KGMM, Eckel RH, Grundy SM et al (2009) Harmonizing the metabolic syndrome: a Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 120:1640–1645. doi: 10.1161/CIRCULATIONAHA.109.192644 CrossRefPubMedGoogle Scholar
  6. 6.
    Grundy SM (2008) Metabolic syndrome pandemic. Arterioscler Thromb Vasc Biol 28:629–636. doi: 10.1161/ATVBAHA.107.151092 CrossRefPubMedGoogle Scholar
  7. 7.
    Vernay M, Salanave B, de Peretti C et al (2013) Metabolic syndrome and socioeconomic status in France: the French Nutrition and Health Survey (ENNS, 2006–2007). Int J Public Health 58:855–864. doi: 10.1007/s00038-013-0501-2 CrossRefPubMedGoogle Scholar
  8. 8.
    Nicklas TA, O’Neil CE, Fulgoni VL (2012) Diet quality is inversely related to cardiovascular risk factors in adults. J Nutr 142:2112–2118. doi: 10.3945/jn.112.164889 CrossRefPubMedGoogle Scholar
  9. 9.
    Lassale C, Galan P, Julia C et al (2013) Association between adherence to nutritional guidelines, the metabolic syndrome and adiposity markers in a French adult general population. PLoS One 8:e76349. doi: 10.1371/journal.pone.0076349 CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Kesse-Guyot E, Ahluwalia N, Lassale C et al (2013) Adherence to Mediterranean diet reduces the risk of metabolic syndrome: a 6-year prospective study. Nutr Metab Cardiovasc Dis 23:677–683. doi: 10.1016/j.numecd.2012.02.005 CrossRefPubMedGoogle Scholar
  11. 11.
    Sabaté J, Wien M (2015) A perspective on vegetarian dietary patterns and risk of metabolic syndrome. Br J Nutr 113:S136–S143. doi: 10.1017/S0007114514004139 CrossRefPubMedGoogle Scholar
  12. 12.
    Veissi M, Anari R, Amani R et al (2016) Mediterranean diet and metabolic syndrome prevalence in type 2 diabetes patients in Ahvaz, southwest of Iran. Diabetes Metab Syndr Clin Res Rev 10:S26–S29. doi: 10.1016/j.dsx.2016.01.015 CrossRefGoogle Scholar
  13. 13.
    He D, Xi B, Xue J et al (2014) Association between leisure time physical activity and metabolic syndrome: a meta-analysis of prospective cohort studies. Endocrine 46:231–240. doi: 10.1007/s12020-013-0110-0 CrossRefPubMedGoogle Scholar
  14. 14.
    Weitzman M (2005) Tobacco smoke exposure is associated with the metabolic syndrome in adolescents. Circulation 112:862–869. doi: 10.1161/CIRCULATIONAHA.104.520650 CrossRefPubMedGoogle Scholar
  15. 15.
    Turner-McGrievy G, Harris M (2014) Key elements of plant-based diets associated with reduced risk of metabolic syndrome. Curr Diab Rep. doi: 10.1007/s11892-014-0524-y CrossRefPubMedGoogle Scholar
  16. 16.
    Aertsens J, Verbeke W, Mondelaers K, Van Huylenbroeck G (2009) Personal determinants of organic food consumption: a review. Br Food J 111:1140–1167. doi: 10.1108/00070700910992961 CrossRefGoogle Scholar
  17. 17.
    Dickson-Spillmann M, Siegrist M, Keller C (2011) Attitudes toward chemicals are associated with preference for natural food. Food Qual Prefer 22:149–156. doi: 10.1016/j.foodqual.2010.09.001 CrossRefGoogle Scholar
  18. 18.
    Michaelidou N, Hassan LM (2008) The role of health consciousness, food safety concern and ethical identity on attitudes and intentions towards organic food. Int J Consum Stud 32:163–170. doi: 10.1111/j.1470-6431.2007.00619.x CrossRefGoogle Scholar
  19. 19.
    Agence Bio/CSA (2016) Baromètre de consommation et de perception des produits biologiques en France, 13ème édition. Accessed 11 Aug 2016
  20. 20.
    Regulation C (2007) No 834/2007 of 28 June 2007 on organic production and labelling of organic products and repealing Regulation (EEC) No 2092/91. Off J Eur Union L 189(1):1–23Google Scholar
  21. 21.
    European Food Safety Authority (2015) The 2013 European Union report on pesticide residues in food: the 2013 European Union report on pesticide residues. EFSA J 13:4038. doi: 10.2903/j.efsa.2015.4038 CrossRefGoogle Scholar
  22. 22.
    Oates L, Cohen M, Braun L et al (2014) Reduction in urinary organophosphate pesticide metabolites in adults after a week-long organic diet. Environ Res 132:105–111. doi: 10.1016/j.envres.2014.03.021 CrossRefPubMedGoogle Scholar
  23. 23.
    Curl CL, Fenske RA, Elgethun K (2002) Organophosphorus pesticide exposure of urban and suburban preschool children with organic and conventional diets. Environ Health Perspect 111:377–382. doi: 10.1289/ehp.5754 CrossRefGoogle Scholar
  24. 24.
    Bradman A, Quirós-Alcalá L, Castorina R et al (2015) Effect of organic diet intervention on pesticide exposures in young children living in low-income urban and agricultural communities. Environ Health Perspect. doi: 10.1289/ehp.1408660 CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Lu C, Toepel K, Irish R et al (2006) Organic diets significantly lower children’s dietary exposure to organophosphorus pesticides. Environ Health Perspect 114:260–263. doi: 10.1289/ehp.8418 CrossRefPubMedGoogle Scholar
  26. 26.
    Barański M, Średnicka-Tober D, Volakakis N et al (2014) Higher antioxidant and lower cadmium concentrations and lower incidence of pesticide residues in organically grown crops: a systematic literature review and meta-analyses. Br J Nutr. doi: 10.1017/S0007114514001366 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Brantsæter AL, Ydersbond TA, Hoppin JA et al (2017) Organic food in the diet: exposure and health implications. Annu Rev Public Health 38:295–313. doi: 10.1146/annurev-publhealth-031816-044437 CrossRefPubMedGoogle Scholar
  28. 28.
    Mie A, Kesse-Guyot E, Rembiałkowska E et al (2016) Human health implications of organic food and organic agriculture. Report No.: EPRS_STU(2016)581922Google Scholar
  29. 29.
    Smith-Spangler C, Brandeau ML, Hunter GE et al (2012) Are organic foods safer or healthier than conventional alternatives? A systematic review. Ann Intern Med 157:348–366. doi: 10.7326/0003-4819-157-5-201209040-00007 CrossRefPubMedGoogle Scholar
  30. 30.
    Brandt K, Leifert C, Sanderson R, Seal CJ (2011) Agroecosystem management and nutritional quality of plant foods: the case of organic fruits and vegetables. Crit Rev Plant Sci 30:177–197. doi: 10.1080/07352689.2011.554417 CrossRefGoogle Scholar
  31. 31.
    Palupi E, Jayanegara A, Ploeger A, Kahl J (2012) Comparison of nutritional quality between conventional and organic dairy products: a meta-analysis. J Sci Food Agric 92:2774–2781. doi: 10.1002/jsfa.5639 CrossRefPubMedGoogle Scholar
  32. 32.
    Średnicka-Tober D, Barański M, Seal CJ et al (2016) Higher PUFA and n-3 PUFA, conjugated linoleic acid, α-tocopherol and iron, but lower iodine and selenium concentrations in organic milk: a systematic literature review and meta- and redundancy analyses. Br J Nutr 115:1043–1060. doi: 10.1017/S0007114516000349 CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Lairon D (2010) Nutritional quality and safety of organic food. A review. Agron Sustain Dev 30:33–41. doi: 10.1051/agro/2009019 CrossRefGoogle Scholar
  34. 34.
    Evangelou E, Ntritsos G, Chondrogiorgi M et al (2016) Exposure to pesticides and diabetes: a systematic review and meta-analysis. Environ Int 91:60–68. doi: 10.1016/j.envint.2016.02.013 CrossRefPubMedGoogle Scholar
  35. 35.
    Nicolopoulou-Stamati P, Maipas S, Kotampasi C et al (2016) Chemical pesticides and human health: the urgent need for a new concept in agriculture. Front Public Health. doi: 10.3389/fpubh.2016.00148 CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Kim K-H, Kabir E, Jahan SA (2017) Exposure to pesticides and the associated human health effects. Sci Total Environ 575:525–535. doi: 10.1016/j.scitotenv.2016.09.009 CrossRefPubMedGoogle Scholar
  37. 37.
    Mostafalou S, Abdollahi M (2017) Pesticides: an update of human exposure and toxicity. Arch Toxicol 91:549–599. doi: 10.1007/s00204-016-1849-x CrossRefPubMedGoogle Scholar
  38. 38.
    Collectif INSERM (2013) Pesticides: Effets sur la santé, une expertise collective de l’Inserm. In: Salle Presse Inserm. Accessed 21 Aug 2016
  39. 39.
    Mnif W, Hassine AIH, Bouaziz A et al (2011) Effect of endocrine disruptor pesticides: a review. Int J Environ Res Public Health 8:2265–2303. doi: 10.3390/ijerph8062265 CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Mozaffarian D, Wu JHY (2011) Omega-3 fatty acids and cardiovascular disease. J Am Coll Cardiol 58:2047–2067. doi: 10.1016/j.jacc.2011.06.063 CrossRefPubMedGoogle Scholar
  41. 41.
    Pan A, Chen M, Chowdhury R et al (2012) Linolenic acid and risk of cardiovascular disease: a systematic review and meta-analysis. Am J Clin Nutr 96:1262–1273. doi: 10.3945/ajcn.112.044040 CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Del Rio D, Rodriguez-Mateos A, Spencer JPE et al (2013) Dietary (Poly)phenolics in human health: structures, bioavailability, and evidence of protective effects against chronic diseases. Antioxid Redox Signal 18:1818–1892. doi: 10.1089/ars.2012.4581 CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Solenkova NV, Newman JD, Berger JS et al (2014) Metal pollutants and cardiovascular disease: mechanisms and consequences of exposure. Am Heart J 168:812–822. doi: 10.1016/j.ahj.2014.07.007 CrossRefPubMedPubMedCentralGoogle Scholar
  44. 44.
    Hord NG, Conley MN (2017) Regulation of dietary nitrate and nitrite: balancing essential physiological roles with potential health risks. In: Bryan NS, Loscalzo J (eds) Nitrite Nitrate Hum. Health Dis. Springer International Publishing, Cham, pp 153–162CrossRefGoogle Scholar
  45. 45.
    Ahluwalia A, Gladwin M, Coleman GD et al (2016) Dietary nitrate and the epidemiology of cardiovascular disease: report From a National Heart, Lung, and Blood Institute Workshop. J Am Heart Assoc 5:e003402. doi: 10.1161/JAHA.116.003402 CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Kesse-Guyot E, Péneau S, Méjean C et al (2013) Profiles of organic food consumers in a large sample of French adults: results from the Nutrinet-Santé Cohort Study. PLoS One 8:e76998. doi: 10.1371/journal.pone.0076998 CrossRefPubMedPubMedCentralGoogle Scholar
  47. 47.
    Eisinger-Watzl M, Wittig F, Heuer T, Hoffmann I (2015) Customers purchasing organic food—do they live healthier? Results of the German National Nutrition Survey II. Eur J Nutr Food Saf 5:59–71. doi: 10.9734/EJNFS/2015/12734 CrossRefGoogle Scholar
  48. 48.
    Kesse-Guyot E, Baudry J, Assmann KE et al (2017) Prospective association between consumption frequency of organic food and body weight change, risk of overweight or obesity: Results from the NutriNet-Santé Study. Br. J, NutrGoogle Scholar
  49. 49.
    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. doi: 10.1186/1471-2458-10-242 CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Kesse-Guyot E, Castetbon K, Touvier M et al (2010) Relative validity and reproducibility of a food frequency questionnaire designed for French adults. Ann Nutr Metab 57:153–162. doi: 10.1159/000321680 CrossRefPubMedGoogle Scholar
  51. 51.
    Baudry J, Méjean C, Allès B et al (2015) Contribution of organic food to the diet in a large sample of French adults (the NutriNet-Santé Cohort Study). Nutrients 7:8615–8632. doi: 10.3390/nu7105417 CrossRefPubMedPubMedCentralGoogle Scholar
  52. 52.
    NutriNet-Santé coordination (2013) Table de composition des aliments - Etude NutriNet-Santé. Economica, ParisGoogle Scholar
  53. 53.
    Baudry J, Allès B, Péneau S et al (2016) Dietary intakes and diet quality according to levels of organic food consumption by French adults: cross-sectional findings from the NutriNet-Santé Cohort Study. Public Health Nutr. doi: 10.1017/S1368980016002718 CrossRefPubMedGoogle Scholar
  54. 54.
    Hagströmer M, Oja P, Sjöström M (2006) The International Physical Activity Questionnaire (IPAQ): a study of concurrent and construct validity. Public Health Nutr 9:755–762CrossRefGoogle Scholar
  55. 55.
    Craig CL, Marshall AL, Sjöström M et al (2003) International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc 35:1381–1395. doi: 10.1249/01.MSS.0000078924.61453.FB CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    INSEE (2009) Definitions and methods. Accessed 21 Aug 2016  
  57. 57.
    Planella T, Cortés M, Martínez-Brú C et al (1997) Calculation of LDL-cholesterol by using apolipoprotein B for classification of nonchylomicronemic dyslipemia. Clin Chem 43:808–815PubMedGoogle Scholar
  58. 58.
    Zhang J, Yu KF (1998) What’s the relative risk?: a method of correcting the odds ratio in cohort studies of common outcomes. JAMA 280:1690. doi: 10.1001/jama.280.19.1690 CrossRefPubMedGoogle Scholar
  59. 59.
    Zou G (2004) A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol 159:702–706. doi: 10.1093/aje/kwh090 CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Curl CL, Beresford SAA, Fenske RA et al (2015) Estimating pesticide exposure from dietary intake and organic food choices: the Multi-Ethnic Study of Atherosclerosis (MESA). Environ Health Perspect. doi: 10.1289/ehp.1408197 CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Wang J, Zhu Y, Cai X et al (2011) Abnormal glucose regulation in pyrethroid pesticide factory workers. Chemosphere 82:1080–1082. doi: 10.1016/j.chemosphere.2010.10.065 CrossRefPubMedGoogle Scholar
  62. 62.
    Montgomery MP, Kamel F, Saldana TM et al (2008) Incident diabetes and pesticide exposure among licensed pesticide applicators: agricultural Health Study, 1993–2003. Am J Epidemiol 167:1235–1246. doi: 10.1093/aje/kwn028 CrossRefPubMedPubMedCentralGoogle Scholar
  63. 63.
    Mostafalou S, Abdollahi M (2013) Pesticides and human chronic diseases: evidences, mechanisms, and perspectives. Toxicol Appl Pharmacol 268:157–177. doi: 10.1016/j.taap.2013.01.025 CrossRefGoogle Scholar
  64. 64.
    Androutsopoulos VP, Hernandez AF, Liesivuori J, Tsatsakis AM (2013) A mechanistic overview of health associated effects of low levels of organochlorine and organophosphorous pesticides. Toxicology 307:89–94. doi: 10.1016/j.tox.2012.09.011 CrossRefPubMedGoogle Scholar
  65. 65.
    Średnicka-Tober D, Barański M, Gromadzka-Ostrowska J et al (2013) Effect of crop protection and fertilization regimes used in organic and conventional production systems on feed composition and physiological parameters in rats. J Agric Food Chem 61:1017–1029. doi: 10.1021/jf303978n CrossRefPubMedGoogle Scholar
  66. 66.
    Średnicka-Tober D, Barański M, Seal C et al (2016) Composition differences between organic and conventional meat: a systematic literature review and meta-analysis. Br J Nutr 115:994–1011. doi: 10.1017/S0007114515005073 CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    Andreeva V, 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. doi: 10.1136/jech-2014-205263 CrossRefPubMedGoogle Scholar
  68. 68.
    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. doi: 10.1093/aje/kww016 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Julia Baudry
    • 1
    Email author
  • Hélène Lelong
    • 1
  • Solia Adriouch
    • 1
  • Chantal Julia
    • 1
  • Benjamin Allès
    • 1
  • Serge Hercberg
    • 1
    • 2
  • Mathilde Touvier
    • 1
  • Denis Lairon
    • 3
  • Pilar Galan
    • 1
  • Emmanuelle Kesse-Guyot
    • 1
  1. 1.Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Centre d’Epidémiologie et Statistiques Sorbonne Paris Cité, Inserm U1153, Inra U1125, Cnam, COMUE Sorbonne Paris Cité, Université Paris 13BobignyFrance
  2. 2.Département de Santé PubliqueHôpital AvicenneBobignyFrance
  3. 3.Aix Marseille Université, Nutrition Obésité et Risque Thrombotique (NORT), Inra 1260, Inserm UMR S 1062MarseilleFrance

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