Food and Agriculture Organization. WHO. Rome: Sustainable healthy diets. Sustainable Healthy Diets—Guiding Principles; 2019.

Google Scholar 

Turner C, Aggarwal A, Walls H, Herforth A, Drewnowski A, Coates J, et al. Concepts and critical perspectives for food environment research: a global framework with implications for action in low- and middle-income countries. Glob Food Sec. 2018;18:93–101.

Article  Google Scholar 

Afshin A, Sur PJ, Fay KA, Cornaby L, Ferrara G, Salama JS, et al. Health effects of dietary risks in 195 countries, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2019;393(10184):1958–72.

Article  Google Scholar 

Segovia-Siapco G, Burkholder-Cooley N, Haddad Tabrizi S, Sabaté J. Beyond meat: a comparison of the dietary intakes of vegetarian and non-vegetarian adolescents. Front Nutr. 2019;6(June):1–11.

Google Scholar 

Kamiński M, Skonieczna-Żydecka K, Nowak JK, Stachowska E. Global and local diet popularity rankings, their secular trends, and seasonal variation in Google Trends data. Nutrition. 2020;79:110759.

Article  PubMed  Google Scholar 

Harland J, Garton L. An update of the evidence relating to plant-based diets and cardiovascular disease, type 2 diabetes and overweight. Nutr Bull. 2016;41(4):323–38.

Article  Google Scholar 

Aleksandrowicz L, Green R, Joy EJM, Smith P, Haines A. The impacts of dietary change on greenhouse gas emissions, land use, water use, and health: a systematic review. PLoS ONE. 2016;11(11):1–16.

Article  Google Scholar 

Nelson ME, Hamm MW, Hu FB, Abrams SA, Griffin TS. Alignment of healthy dietary patterns and environmental sustainability: a systematic review. Adv Nutr. 2016;7(6):1005–25.

Article  PubMed  PubMed Central  Google Scholar 

Fresán U, Sabaté J. Vegetarian diets: planetary health and its alignment with human health. Adv Nutr. 2019;10:S380–8.

Article  PubMed  PubMed Central  Google Scholar 

Hemler EC, Hu FB. Plant-based diets for personal, population, and planetary health. Adv Nutr. 2019;10(6):S275–83.

Article  PubMed  PubMed Central  Google Scholar 

Willett W, Rockström J, Loken B, Springmann M, Lang T, Vermeulen S, et al. Food in the anthropocene: the EAT–lancet commission on healthy diets from sustainable food systems. Lancet. 2019;393(10170):447–92.

Article  PubMed  Google Scholar 

Semba RD, de Pee S, Kim B, McKenzie S, Nachman K, Bloem MW. Adoption of the ‘planetary health diet’ has different impacts on countries’ greenhouse gas emissions. Nat Food. 2020;1(8):481–4. https://doi.org/10.1038/s43016-020-0128-4.

Article  PubMed  Google Scholar 

Tuninetti M, Ridolfi L, Laio F. Compliance with EAT–Lancet dietary guidelines would reduce global water footprint but increase it for 40% of the world population. Nat Food. 2022;3(2):143–51.

Article  PubMed  Google Scholar 

Batis C, Marrón-Ponce JA, Stern D, Vandevijvere S, Barquera S, Rivera JA. Adoption of healthy and sustainable diets in Mexico does not imply higher expenditure on food. Nat Food. 2021;2(10):792–801.

Article  PubMed  Google Scholar 

Knuppel A, Papier K, Key TJ, Travis RC. EAT-Lancet score and major health outcomes: the EPIC-Oxford study. Lancet. 2019;394(10194):213–4. https://doi.org/10.1016/S0140-6736(19)31236-X.

Article  PubMed  Google Scholar 

Cacau LT, Benseñor IM, Goulart AC, de Cardoso O, Lotufo PA, Moreno LA, et al. Adherence to the planetary health diet index and obesity indicators in the Brazilian longitudinal study of adult health (ELSA-Brasil). Nutrients. 2021;13(11):1–12.

Article  Google Scholar 

Ahmad SR. Plant-based diet for obesity treatment. Front Nutr. 2022. https://doi.org/10.3389/fnut.2022.952553.

Article  PubMed  PubMed Central  Google Scholar 

Pérusse L, Jacob R, Drapeau V, Llewellyn C, Arsenault BJ, Bureau A, et al. Understanding gene-lifestyle interaction in obesity: the role of mediation versus moderation. Lifestyle Genomics. 2022;15(2):67–76.

Article  PubMed  Google Scholar 

Masip G, Silventoinen K, Keski-Rahkonen A, Palviainen T, Sipilä PN, Kaprio J, et al. The genetic architecture of the association between eating behaviors and obesity: combining genetic twin modeling and polygenic risk scores. Am J Clin Nutr. 2020;112(4):956–66.

Article  PubMed  PubMed Central  Google Scholar 

Jacob R, Bertrand C, Llewellyn C, Couture C, Labonté MÈ, Tremblay A, et al. Dietary mediators of the genetic susceptibility to obesity—results from the Quebec family study. J Nutr. 2022;152(1):49–58.

Article  PubMed  Google Scholar 

Heianza Y, Zhou T, Sun D, Hu FB, Qi L. Healthful plant-based dietary patterns, genetic risk of obesity, and cardiovascular risk in the UK biobank study. Clin Nutr. 2021;40(7):4694–701.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Masip G, Attar A, Nielsen DE. Plant-based dietary patterns and genetic susceptibility to obesity in the CARTaGENE cohort. Obesity. 2024;32(2):409–22.

Article  PubMed  CAS  Google Scholar 

Suikki T, Maukonen M, Marjonen-Lindblad H, Kaartinen NE, Härkänen T, Jousilahti P, et al. Role of planetary health diet in the association between genetic susceptibility to obesity and anthropometric measures in adults. Int J Obes. 2024. https://doi.org/10.1038/s41366-024-01656-7.

Article  Google Scholar 

Awadalla P, Boileau C, Payette Y, Idaghdour Y, Goulet JP, Knoppers B, et al. Cohort profile of the CARTaGENE study: Quebec’s population-based biobank for public health and personalized genomics. Int J Epidemiol. 2013;42(5):1285–99.

Article  PubMed  Google Scholar 

Parr CL, Hjartåker A, Scheel I, Lund E, Laake P, Veierød MB. Comparing methods for handling missing values in food-frequency questionnaires and proposing k nearest neighbours imputation: effects on dietary intake in the Norwegian Women and Cancer study (NOWAC). Public Health Nutr. 2008;11(4):361–70.

Article  PubMed  Google Scholar 

Karin M, Willett W. Self-administered semiquantitative food frequency questionnaires: patterns, predictors, and interpretation of omitted items. Epidemiology. 2009;20(2):295–301.

Article  Google Scholar 

Horne JR, Gilliland J, Madill J. Assessing the validity of the past-month, online canadian diet history questionnaire ii pre and post nutrition intervention. Nutrients. 2020;12(5):1454.

Article  PubMed  PubMed Central  Google Scholar 

Cacau LT, De Carli E, de Carvalho AM, Lotufo PA, Moreno LA, Bensenor IM, et al. Development and validation of an index based on eat-lancet recommendations: the planetary health diet index. Nutrients. 2021;13(5):1698.

Article  PubMed  PubMed Central  Google Scholar 

Duhazé J, Jantzen R, Payette Y, De Malliard T, Labbé C, Noisel N, et al. Quantifying the predictive accuracy of a polygenic risk score for predicting incident cancer cases : application to the CARTaGENE cohort. Front Genet. 2020;11(April):1–14.

Google Scholar 

Khera AV, Chaffin M, Wade KH, Zahid S, Brancale J, Xia R, et al. Polygenic prediction of weight and obesity trajectories from birth to adulthood. Cell. 2019;177(3):587–96. https://doi.org/10.1016/j.cell.2019.03.028.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518(7538):197–206.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Dashti HS, Miranda N, Cade BE, Huang T, Redline S, Karlson EW, et al. Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank. BMC Med. 2022;20(1):1–12.

Article  Google Scholar 

Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904–9.

Article  PubMed  CAS  Google Scholar 

Cancello R, Soranna D, Brunani A, Scacchi M, Tagliaferri A, Mai S, et al. Analysis of predictive equations for estimating resting energy expenditure in a large cohort of morbidly obese patients. Front Endocrinol. 2018;9:1–8.

Article  Google Scholar 

Garriguet D. Impact of identifying plausible respondents on the under-reporting of energy intake in the Canadian community health survey. Heal Reports. 2008;19(4):47.

Google Scholar 

Stekhoven DJ, Bühlmann P. Missforest-Non-parametric missing value imputation for mixed-type data. Bioinformatics. 2012;28(1):112–8.