Skip to main content

Thank you for visiting 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.

Prevention of Non Communicable Diseases

Palaeolithic diet score and risk of breast cancer among postmenopausal women overall and by hormone receptor and histologic subtypes



The Palaeolithic diet (PD) has gained popularity globally. There is emerging evidence of its putative health benefits as short-term effects on chronic diseases have been reported. We evaluated the association between long-term adherence to the PD and breast cancer (BC) risk among postmenopausal women.


65,574 women from the Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l’Education Nationale (E3N) cohort were followed from 1993 to 2014. Incident BC cases were identified and validated. The PD score was calculated using dietary intake self-reported at baseline (1993) and follow-up (2005) or baseline only if censored before follow-up. Multivariable Cox proportional hazards regression models were used to estimate BC hazard ratios (HR) and 95% confidence intervals (CI).


Over a mean follow-up of 20 years, 3968 incident BC cases occurred. An increase of 1 standard deviation in the PD score was associated with an 8% lower BC risk, fully-adjusted model: HR1-SD 0.92, 95% CI; 0.89, 0.95. Compared to women with low adherence to the PD, women with high adherence had a 17% lower BC risk, HRQ5 vs Q1 0.83, 95% CI; 0.75, 0.92, Ptrend < 0.01. When considering BC subtypes, we observed the same pattern of association (Pheterogeneity > 0.10 for all).


High adherence to a PD characterised by fruit, vegetables, nuts, fish, and lean meat and limited in dairy, grains, legumes, refined sugar, and alcohol was associated with a lower BC risk. The lack of heterogeneity according to BC subtypes could indicate the involvement of non-hormonal mechanisms. The protocol is registered at as NCT03285230.


The protocol is registered at as NCT03285230.

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

Access options

Rent or buy this article

Get just this article for as long as you need it


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

Fig. 1: The Palaeolithic diet score and breast cancer risk, overall and by subtypes among postmenopausal women, E3N cohort (N = 65,574).
Fig. 2: Associations of the Palaeolithic diet score with breast cancer fitted with restricted cubic splines (5 knots placed at the 5th, 27.5th, 50th, 72.5th, and 95th percentiles).

Data availability

The datasets generated during and/or analysed for the current study are available from the corresponding author upon reasonable request.


  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49.

    Article  Google Scholar 

  2. Azamjah N, Soltan-Zadeh Y, Zayeri F. Global trend of breast cancer mortality rate: a 25-year study. Asian Pac J Cancer Prev. 2019;20:2015–20.

    Article  Google Scholar 

  3. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68:394–424.

    Article  Google Scholar 

  4. Fitzmaurice C. Global Burden of Disease Cancer C. Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-adjusted life-years for 29 cancer groups, 2006 to 2016: A systematic analysis for the Global Burden of Disease study. J Clin Oncol. 2018;36:1553–68.

    Article  Google Scholar 

  5. Sharma R. Breast cancer incidence, mortality and mortality-to-incidence ratio (MIR) are associated with human development, 1990-2016: evidence from Global Burden of Disease Study 2016. Breast Cancer. 2019;26:428–45.

    Article  Google Scholar 

  6. Institute of M, National Research Council National Cancer Policy B. Fulfilling the Potential of Cancer Prevention and Early Detection. Washington (DC): National Academies Press (US); 2014 2014/07/25/.

  7. Ghaedi E, Mohammadi M, Mohammadi H, Ramezani-Jolfaie N, Malekzadeh J, Hosseinzadeh M, et al. Effects of a paleolithic diet on cardiovascular disease risk factors: a systematic review and meta-analysis of randomized controlled trials. Adv Nutr. 2019;10:634–46.

    Article  Google Scholar 

  8. Jönsson T, Granfeldt Y, Ahrén B, Branell U, Pålsson G, Hansson A. Beneficial effects of a Paleolithic diet on cardiovascular risk factors in type 2 diabetes: a randomized cross-over pilot study. Cardiovasc Diabetol. 2009;8:35.

    Article  Google Scholar 

  9. Manheimer EW, van Zuuren EJ, Fedorowicz Z, Pijl H. Paleolithic nutrition for metabolic syndrome: systematic review and meta-analysis. Am J Clin Nutr. 2015;102:922–32.

    Article  CAS  Google Scholar 

  10. Whalen KA, McCullough M, Flanders WD, Hartman TJ, Judd S, Bostick RM. Paleolithic and mediterranean diet pattern scores and risk of incident, sporadic colorectal adenomas. Am J Epidemiol. 2014;180:1088–97.

    Article  Google Scholar 

  11. Kushi LH, Potter JD, Bostick RM, Drinkard CR, Sellers TA, Gapstur SM, et al. Dietary fat and risk of breast cancer according to hormone receptor status. Cancer Epidemiol Biomark Prev. 1995;4:11–9.

    CAS  Google Scholar 

  12. Olsen A, Tjonneland A, Thomsen BL, Loft S, Stripp C, Overvad K, et al. Fruits and vegetables intake differentially affects estrogen receptor negative and positive breast cancer incidence rates. J Nutr. 2003;133:2342–7.

    Article  CAS  Google Scholar 

  13. Zhang SM, Hankinson SE, Hunter DJ, Giovannucci EL, Colditz GA, Willett WC. Folate intake and risk of breast cancer characterized by hormone receptor status. Cancer Epidemiol Biomark Prev. 2005;14:2004–8.

    Article  CAS  Google Scholar 

  14. Fung TT, Hu FB, Holmes MD, Rosner BA, Hunter DJ, Colditz GA, et al. Dietary patterns and the risk of postmenopausal breast cancer. Int J Cancer. 2005;116:116–21.

    Article  CAS  Google Scholar 

  15. Shin S, Saito E, Inoue M, Sawada N, Ishihara J, Takachi R, et al. Dietary pattern and breast cancer risk in Japanese women: the Japan Public Health Center-based Prospective Study (JPHC Study). Br J Nutr. 2016;115:1769–79.

    Article  CAS  Google Scholar 

  16. Velie EM, Schairer C, Flood A, He J-P, Khattree R, Schatzkin A. Empirically derived dietary patterns and risk of postmenopausal breast cancer in a large prospective cohort study. Am J Clin Nutr. 2005;82:1308–19.

    Article  CAS  Google Scholar 

  17. Mannisto S, Harald K, Harkanen T, Maukonen M, Eriksson JG, Heikkinen S, et al. Association between overall diet quality and postmenopausal breast cancer risk in five Finnish cohort studies. Sci Rep. 2021;11:16718.

    Article  CAS  Google Scholar 

  18. Haridass V, Ziogas A, Neuhausen SL, Anton-Culver H, Odegaard AO. Diet quality scores inversely associated with postmenopausal breast cancer risk are not associated with premenopausal breast cancer risk in the California teachers study. J Nutr. 2018;148:1830–7.

    Article  Google Scholar 

  19. Clavel-Chapelon F. Cohort profile: the French E3N cohort study. Int J Epidemiol. 2015;44:801–9.

    Article  Google Scholar 

  20. Cottet V, Touvier M, Fournier A, Touillaud MS, Lafay L, Clavel-Chapelon F, et al. Postmenopausal breast cancer risk and dietary patterns in the E3N-EPIC prospective cohort study. Am J Epidemiol. 2009;170:1257–67.

    Article  Google Scholar 

  21. Lucas F, Niravong M, Villeminot S, Kaaks R, Clavel-Chapelon F. Estimation of food portion size using photographs: validity, strengths, weaknesses and recommendations. J Hum Nutr Dietetics. 1995;8:65–74.

    Article  Google Scholar 

  22. van Liere M. Relative validity and reproducibility of a French dietary history questionnaire. Int J Epidemiol. 1997;26:128S–36.

    Article  Google Scholar 

  23. Jean-Claude F, Jayne I, Carole T, Max F. Répertoire général des aliments - Table de composition. 2nd ed. Paris (FRA):Inra;1995.

  24. Food and Agriculture Organization of the United Nations. Guidelines for measuring household and individual dietary diversity 2013. Available from:

  25. Shah S, MacDonald CJ, El Fatouhi D, Mahamat-Saleh Y, Mancini FR, Fagherazzi G, et al. The associations of the Palaeolithic diet alone and in combination with lifestyle factors with type 2 diabetes and hypertension risks in women in the E3N prospective cohort. Eur J Nutr. 2021;60:3935–45.

    Article  CAS  Google Scholar 

  26. Tehard B, van Liere MJ, Com Nougue C, Clavel-Chapelon F. Anthropometric measurements and body silhouette of women: validity and perception. J Am Diet Assoc. 2002;102:1779–84.

    Article  CAS  Google Scholar 

  27. Harrell FE. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis: Springer; 2013.

  28. Allison PD. Survival Analysis Using SAS®: A Practical Guide, Second Edition. Cary, NC: SAS Institute Inc. 2010.

  29. Bagnardi V, Rota M, Botteri E, Tramacere I, Islami F, Fedirko V, et al. Alcohol consumption and site-specific cancer risk: a comprehensive dose-response meta-analysis. Br J Cancer. 2015;112:580–93.

    Article  CAS  Google Scholar 

  30. Cordain L. The nutritional characteristics of a contemporary diet based upon Paleolithic food groups. J Am Nutraceutical Assoc. 2002;5:15–24.

    Google Scholar 

  31. Frassetto LA, Schloetter M, Mietus-Synder M, Morris RC Jr, Sebastian A. Metabolic and physiologic improvements from consuming a paleolithic, hunter-gatherer type diet. Eur J Clin Nutr. 2009;63:947–55.

    Article  CAS  Google Scholar 

  32. Osterdahl M, Kocturk T, Koochek A, Wandell PE. Effects of a short-term intervention with a paleolithic diet in healthy volunteers. Eur J Clin Nutr. 2008;62:682–5.

    Article  CAS  Google Scholar 

  33. Bisht B, Darling WG, Grossmann RE, Shivapour ET, Lutgendorf SK, Snetselaar LG, et al. A multimodal intervention for patients with secondary progressive multiple sclerosis: feasibility and effect on fatigue. J Alter Complement Med. 2014;20:347–55.

    Article  Google Scholar 

  34. Bligh HF, Godsland IF, Frost G, Hunter KJ, Murray P, MacAulay K, et al. Plant-rich mixed meals based on Palaeolithic diet principles have a dramatic impact on incretin, peptide YY and satiety response, but show little effect on glucose and insulin homeostasis: an acute-effects randomised study. Br J Nutr. 2015;113:574–84.

    Article  Google Scholar 

  35. Whalen KA, McCullough ML, Dana Flanders W, Hartman TJ, Judd S, Bostick RM. Paleolithic and mediterranean diet pattern scores are inversely associated with biomarkers of inflammation and oxidative balance in adults. J Nutr. 2016;146:1217–26.

    Article  CAS  Google Scholar 

  36. Whalen K, Judd S, McCullough M, Flanders W, Hartman T, Bostick R. Paleolithic and mediterranean diet pattern scores are inversely associated with all-cause and cause-specific mortality in adults. J Nutr. 2017;147:612–20.

    Article  CAS  Google Scholar 

  37. Jospe MR, Roy M, Brown RC, Haszard JJ, Meredith-Jones K, Fangupo LJ, et al. Intermittent fasting, Paleolithic, or Mediterranean diets in the real world: exploratory secondary analyses of a weight-loss trial that included choice of diet and exercise. Am J Clin Nutr. 2020;111:503–14.

    Article  Google Scholar 

  38. Klement RJ, Koebrunner PS, Krage K, Weigel MM, Sweeney RA. Short-term effects of a Paleolithic lifestyle intervention in breast cancer patients undergoing radiotherapy: a pilot and feasibility study. Med Oncol. 2020;38:1.

    Article  Google Scholar 

  39. Ben-Dor M, Sirtoli R, Barkai R. The evolution of the human trophic level during the Pleistocene. Am J Phys Anthropol. 2021;175:27–56.

    Article  Google Scholar 

  40. Spreadbury I. Comparison with ancestral diets suggests dense acellular carbohydrates promote an inflammatory microbiota, and may be the primary dietary cause of leptin resistance and obesity. Diabetes Metab Syndr Obes. 2012;5:175–89.

    Article  CAS  Google Scholar 

  41. Roberts DL, Dive C, Renehan AG. Biological mechanisms linking obesity and cancer risk: new perspectives. Annu Rev Med. 2010;61:301–16.

    Article  CAS  Google Scholar 

  42. Debras C, Chazelas E, Srour B, Kesse-Guyot E, Julia C, Zelek L, et al. Total and added sugar intakes, sugar types, and cancer risk: results from the prospective NutriNet-Sante cohort. Am J Clin Nutr. 2020;112:1267–79.

    Article  Google Scholar 

  43. Fiolet T, Srour B, Sellem L, Kesse-Guyot E, Alles B, Mejean C, et al. Consumption of ultra-processed foods and cancer risk: results from NutriNet-Sante prospective cohort. BMJ. 2018;360:k322.

    Article  Google Scholar 

  44. Otten J, Stomby A, Waling M, Isaksson A, Tellstrom A, Lundin-Olsson L, et al. Benefits of a Paleolithic diet with and without supervised exercise on fat mass, insulin sensitivity, and glycemic control: a randomized controlled trial in individuals with type 2 diabetes. Diabetes Metab Res Rev. 2017;33:e2828.

  45. Stoll BA. Western nutrition and the insulin resistance syndrome: a link to breast cancer. Eur J Clin Nutr. 1999;53:83–7.

    Article  CAS  Google Scholar 

  46. Bao Y, Han J, Hu FB, Giovannucci EL, Stampfer MJ, Willett WC, et al. Association of nut consumption with total and cause-specific mortality. N. Engl J Med. 2013;369:2001–11.

    Article  CAS  Google Scholar 

  47. Lampe JW. Health effects of vegetables and fruit: assessing mechanisms of action in human experimental studies. Am J Clin Nutr. 1999;70:475S–90S.

    Article  CAS  Google Scholar 

  48. Radzikowska U, Rinaldi AO, Celebi Sozener Z, Karaguzel D, Wojcik M, Cypryk K, et al. The influence of dietary fatty acids on immune responses. Nutrients. 2019;11:2990.

    Article  CAS  Google Scholar 

  49. Chen S, Chen Y, Ma S, Zheng R, Zhao P, Zhang L, et al. Dietary fibre intake and risk of breast cancer: A systematic review and meta-analysis of epidemiological studies. Oncotarget. 2016;7:80980–9.

    Article  Google Scholar 

  50. Dallal CM, Lacey JV Jr, Pfeiffer RM, Bauer DC, Falk RT, Buist DS, et al. Estrogen metabolism and risk of postmenopausal endometrial and ovarian cancer: the B approximately FIT cohort. Horm Cancer. 2016;7:49–64.

    Article  CAS  Google Scholar 

  51. Cummings JH, Mann JI, Nishida C, Vorster HH. Dietary fibre: an agreed definition. Lancet. 2009;373:365–6.

    Article  CAS  Google Scholar 

  52. de Punder K, Pruimboom L. The dietary intake of wheat and other cereal grains and their role in inflammation. Nutrients. 2013;5:771–87.

    Article  Google Scholar 

  53. Cordain L. Cereal grains: humanity’s double-edged sword. World Rev Nutr Diet. 1999;84:19–73.

    Article  CAS  Google Scholar 

  54. McAfee AJ, McSorley EM, Cuskelly GJ, Moss BW, Wallace JMW, Bonham MP, et al. Red meat consumption: an overview of the risks and benefits. Meat Sci. 2010;84:1–13.

    Article  CAS  Google Scholar 

  55. Santarelli RL, Pierre F, Corpet DE. Processed meat and colorectal cancer: a review of epidemiologic and experimental evidence. Nutr Cancer. 2008;60:131–44.

    Article  CAS  Google Scholar 

  56. Ward MH, Cross AJ, Divan H, Kulldorff M, Nowell-Kadlubar S, Kadlubar FF, et al. Processed meat intake, CYP2A6 activity and risk of colorectal adenoma. Carcinogenesis. 2007;28:1210–6.

    Article  CAS  Google Scholar 

  57. de Menezes EVA, Sampaio HAC, Carioca AAF, Parente NA, Brito FO, Moreira TMM, et al. Influence of Paleolithic diet on anthropometric markers in chronic diseases: systematic review and meta-analysis. Nutr J. 2019;18:41.

    Article  Google Scholar 

  58. Blomquist C, Chorell E, Ryberg M, Mellberg C, Worrsjö E, Makoveichuk E, et al. Decreased lipogenesis-promoting factors in adipose tissue in postmenopausal women with overweight on a Paleolithic-type diet. Eur J Nutr. 2018;57:2877–86.

    Article  CAS  Google Scholar 

  59. Abdoli A. High salt and fat intake, inflammation, and risk of cancer. Front Biol. 2018;12:387–91.

    Article  Google Scholar 

Download references


The research was carried out using data from INSERM (French National Institutes for Health and Medical Research) E3N cohort, which was established and maintained with the support of the Mutuelle Générale de l’Education Nationale (MGEN), Gustave Roussy, and the French League against Cancer (LNCC). E3N-E4N is also supported by the French National Research Agency (ANR) under the Investment for the Future Programme (PIA) (ANR-10-COHO-0006) and by the French Ministry of Higher Education, Research and Innovation (subsidy for public service charges n°2103 586016). The authors are indebted to all participants for their continued participation. They are also grateful to all members of the E3N study group.


This research was carried out using data from INSERM’S E3N cohort with the support of the MGEN, Institut Gustave Roussy and the “Ligue contre le Cancer” for the constitution and maintenance of the E3N cohort. This work has also benefited from State aid managed by the National Research Agency under the programme “Investissement d’avenir” under the reference ANR-10-COHO-0006 as well as a subsidy from the “Ministère de l’enseignement supérieur de la recherche et de l’innovation” for public service charges under the reference n°2103 586016. SS is supported by a doctoral funding from l’Ecole Doctorale de Santé Publique, Ministère de l’enseignement supérieur, de la recherche et de l’innovation.

Author information

Authors and Affiliations



SS, MCBR, and NL conceived and designed the study. MCBR and NL contributed equally as the last authors. SS performed the statistical analysis and drafted the original manuscript. All authors contributed to the interpretation of data discussed in the manuscript, revised it, and approved its final version to be published. NL is the guarantor of this work and, as such, has full access to all the data in the study and takes responsibility for the integrity of the data and accuracy of the data analysis.

Corresponding author

Correspondence to Marie-Christine Boutron-Ruault.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval

The study participants provided written informed consent, and the cohort study received ethical approval from the French National Commission for Computerized Data and Individual Freedom.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Shah, S., Mahamat-Saleh, Y., Hajji-Louati, M. et al. Palaeolithic diet score and risk of breast cancer among postmenopausal women overall and by hormone receptor and histologic subtypes. Eur J Clin Nutr (2023).

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI:


Quick links