{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:36:16Z","timestamp":1763645776910,"version":"3.45.0"},"reference-count":52,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Secretariat of Science, Humanities, Technology and Innovation (SECIHTI, M\u00e9xico), Investigadores por M\u00e9xico","award":["7186"],"award-info":[{"award-number":["7186"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background: Excessive fructose intake has been linked to adverse metabolic outcomes, yet few studies have comprehensively described the clinical, behavioral, and nutritional patterns associated with different intake levels using machine learning. Methods: In this study, unsupervised and supervised algorithms were applied to a healthy Mexican cohort to examine features related to high fructose consumption, defined as intake above 25 g per day. Results: K-Means clustering identified three distinct profiles, with one subgroup showing less favorable anthropometric, biochemical, and behavioral characteristics. Supervised models, including Extreme Gradient Boosting, Random Forest, and Histogram-based Gradient Boosting, distinguished fructose intake levels with balanced accuracies around 80% and AUC up to 88.1%. Shapley Additive Explanations (SHAPs)-based interpretation highlighted body mass index, triglycerides, sleep duration, alcohol consumption, and anxiety indicators as features most consistently associated with high intake. Conclusions: These findings emphasize the multifactorial nature of fructose consumption and illustrate the utility of machine learning for uncovering dietary and metabolic patterns that warrant further investigation and may guide future nutrition-focused strategies.<\/jats:p>","DOI":"10.3390\/nu17223623","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:25:27Z","timestamp":1763645127000},"page":"3623","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identifying Key Features Associated with Excessive Fructose Intake: A Machine Learning Analysis of a Mexican Cohort"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0090-2701","authenticated-orcid":false,"given":"Guadalupe","family":"Guti\u00e9rrez-Esparza","sequence":"first","affiliation":[{"name":"\u201cResearcher for Mexico\u201d Program, Secretar\u00eda de Ciencia, Humanidades, Tecnolog\u00eda e Innovaci\u00f3n (SECIHTI), Mexico City 03940, Mexico"},{"name":"Diagnostic and Treatment Services, Instituto Nacional de Cardiolog\u00eda Ignacio Ch\u00e1vez, Mexico City 14080, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2876-8500","authenticated-orcid":false,"given":"Mireya","family":"Mart\u00ednez-Garc\u00eda","sequence":"additional","affiliation":[{"name":"Department of Immunology, Instituto Nacional de Cardiolog\u00eda Ignacio Ch\u00e1vez, Mexico City 14080, Mexico"},{"name":"Dental Public Health Department, Division of Graduate Studies and Research, School of Dentistry, Universidad Nacional Aut\u00f3noma de M\u00e9xico, Mexico City 04510, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mar\u00eda del Carmen","family":"Gonz\u00e1lez Salazar","sequence":"additional","affiliation":[{"name":"Department of Nutrition, Ambulatory Care Services, Instituto Nacional de Cardiolog\u00eda Ignacio Ch\u00e1vez, Mexico City 14080, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6258-5732","authenticated-orcid":false,"given":"Luis M.","family":"Amezcua-Guerra","sequence":"additional","affiliation":[{"name":"Department of Immunology, Instituto Nacional de Cardiolog\u00eda Ignacio Ch\u00e1vez, Mexico City 14080, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0238-8278","authenticated-orcid":false,"given":"Malinalli","family":"Brianza-Padilla","sequence":"additional","affiliation":[{"name":"Department of Immunology, Instituto Nacional de Cardiolog\u00eda Ignacio Ch\u00e1vez, Mexico City 14080, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1638-5086","authenticated-orcid":false,"given":"Tania","family":"Ram\u00edrez-delReal","sequence":"additional","affiliation":[{"name":"\u201cResearcher for Mexico\u201d Program, Secretar\u00eda de Ciencia, Humanidades, Tecnolog\u00eda e Innovaci\u00f3n (SECIHTI), Mexico City 03940, Mexico"},{"name":"Centro de Investigaci\u00f3n en Ciencias de Informaci\u00f3n Geoespacial, Aguascalientes 20313, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1872-1397","authenticated-orcid":false,"given":"Enrique","family":"Hern\u00e1ndez-Lemus","sequence":"additional","affiliation":[{"name":"Computational Genomics Division, Instituto Nacional de Medicina Gen\u00f3mica, Mexico City 14610, Mexico"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"949","DOI":"10.3945\/jn.114.190652","article-title":"Caloric beverages were major sources of energy among children and adults in Mexico, 1999\u20132012","volume":"144","author":"Stern","year":"2014","journal-title":"J. Nutr."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Singh, G.M., Micha, R., Khatibzadeh, S., Shi, P., Lim, S., Andrews, K.G., Engell, R.E., Ezzati, M., Mozaffarian, D., and Global Burden of Diseases Nutrition and Chronic Diseases Expert Group (NutriCoDE) (2015). Global, regional, and national consumption of sugar-sweetened beverages, fruit juices, and milk: A systematic assessment of beverage intake in 187 countries. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0124845"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1038\/s41574-021-00627-6","article-title":"The role of sugar-sweetened beverages in the global epidemics of obesity and chronic diseases","volume":"18","author":"Malik","year":"2022","journal-title":"Nat. Rev. Endocrinol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1888S","DOI":"10.3945\/jn.115.220301","article-title":"Sugar-sweetened beverages are the main sources of added sugar intake in the Mexican population","volume":"146","author":"Batis","year":"2016","journal-title":"J. Nutr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1881S","DOI":"10.3945\/jn.115.219121","article-title":"Discretionary foods have a high contribution and fruit, vegetables, and legumes have a low contribution to the total energy intake of the Mexican population","volume":"146","author":"Aburto","year":"2016","journal-title":"J. Nutr."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Cantoral, A., Contreras-Manzano, A., Luna-Villa, L., Batis, C., Rold\u00e1n-Valadez, E.A., Ettinger, A.S., Mercado, A., Peterson, K.E., T\u00e9llez-Rojo, M.M., and Rivera, J.A. (2019). Dietary sources of fructose and its association with fatty liver in mexican young adults. Nutrients, 11.","DOI":"10.3390\/nu11030522"},{"key":"ref_7","unstructured":"World Health Organization (2015). Guideline: Sugars Intake for Adults and Children, World Health Organization."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.gendis.2019.10.001","article-title":"The dark face of fructose as a tumor promoter","volume":"7","author":"Santhekadur","year":"2019","journal-title":"Genes Dis."},{"key":"ref_9","unstructured":"Dommarco, J.\u00c1.R., Aragon\u00e9s, M.A.C., Fuentes, M.L., Mart\u00ednez, T.G.d.C., Salinas, C.A.A., Licona, G.H., and Barquera, S. (2018). La Obesidad en M\u00e9xico. Estado de la Pol\u00edtica P\u00fablica y Recomendaciones Para su Prevenci\u00f3n y Control, Instituto Nacional de Salud P\u00fablica de M\u00e9xico."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"49","DOI":"10.15698\/cst2025.06.305","article-title":"Pathogenic aspects of fructose consumption in metabolic dysfunction-associated steatotic liver disease (MASLD): A narrative review","volume":"9","author":"Burger","year":"2025","journal-title":"Cell Stress"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Muriel, P., L\u00f3pez-S\u00e1nchez, P., and Ramos-Tovar, E. (2021). Fructose and the Liver. Int. J. Mol. Sci., 22.","DOI":"10.3390\/ijms22136969"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Oviedo-Sol\u00eds, C.I., Hern\u00e1ndez-Alcaraz, C., S\u00e1nchez-Ort\u00edz, N.A., L\u00f3pez-Olmedo, N., J\u00e1uregui, A., and Barquera, S. (2022). Association of sociodemographic and lifestyle factors with dietary patterns among men and women living in Mexico City: A cross-sectional study. Front. Public Health, 10.","DOI":"10.3389\/fpubh.2022.859132"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"136915","DOI":"10.1016\/j.foodchem.2023.136915","article-title":"Precise prediction of metabolites patterns using machine learning approaches in distinguishing honey and sugar diets fed to mice","volume":"430","author":"Zheng","year":"2024","journal-title":"Food Chem."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1093\/jn\/nxab341","article-title":"A machine learning approach to predict the added-sugar content of packaged foods","volume":"152","author":"Davies","year":"2022","journal-title":"J. Nutr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"102511","DOI":"10.1016\/j.jcou.2023.102511","article-title":"Parametric analysis and machine learning for enhanced recovery of high-value sugar from date fruits using supercritical CO2 with co-solvents","volume":"72","author":"AlYammahi","year":"2023","journal-title":"J. CO2 Util."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e016773","DOI":"10.1136\/bmjopen-2017-016773","article-title":"Protocol for a prospective longitudinal study of risk factors for hypertension incidence in a Mexico City population: The Tlalpan 2020 cohort","volume":"7","author":"Madero","year":"2017","journal-title":"BMJ Open"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1080\/1740028032000131396","article-title":"Thirty years of bioethics: The Helsinki Declaration 1964\u20132003","volume":"1","author":"Riis","year":"2003","journal-title":"New Rev. Bioeth."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1206","DOI":"10.1161\/01.HYP.0000107251.49515.c2","article-title":"Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure","volume":"42","author":"Chobanian","year":"2003","journal-title":"Hypertension"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"824","DOI":"10.21149\/15654","article-title":"Gender assessment of sleep disorders in an adult urban population of Mexico City","volume":"66","year":"2024","journal-title":"Salud Publica Mexico"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Amezcua-Guerra, L.M., Vel\u00e1zquez-Espinosa, K.P., Pi\u00f1a-Soto, L.A., Guti\u00e9rrez-Esparza, G.O., Mart\u00ednez-Garc\u00eda, M., and Brianza-Padilla, M. (2024). The Self-Reported Quality of Sleep and Its Relationship with the Development of Arterial Hypertension: Perspectives from the Tlalpan 2020 Cohort. J. Clin. Med., 13.","DOI":"10.3390\/jcm13206089"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Stewart, A.L., and Ware, J.E. (1992). Measuring Functioning and Well-Being: The Medical Outcomes Study Approach, Duke University Press.","DOI":"10.7249\/CB361"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1097\/GME.0000000000000835","article-title":"Psychometric properties of the medical outcomes study sleep scale in Spanish postmenopausal women","volume":"24","year":"2017","journal-title":"Menopause"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"268","DOI":"10.3906\/sag-1909-157","article-title":"Turkish reliability and validity study of the medical outcomes study (MOS) sleep scale inpatients with obstructive sleep apnea","volume":"51","author":"Akcay","year":"2021","journal-title":"Turk. J. Med. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"89","DOI":"10.17241\/smr.2011.2.3.89","article-title":"The reliability and validity of the Korean version of the Medical Outcomes Study-Sleep Scale in patients with obstructive sleep apnea","volume":"2","author":"Kim","year":"2011","journal-title":"Sleep Med. Res."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"589","DOI":"10.1037\/h0023769","article-title":"Anxiety (drive), stress, and serial-position effects in serial-verbal learning","volume":"72","author":"Spielberger","year":"1966","journal-title":"J. Exp. Psychol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1381","DOI":"10.1249\/01.MSS.0000078924.61453.FB","article-title":"International physical activity questionnaire: 12-country reliability and validity","volume":"35","author":"Craig","year":"2003","journal-title":"Med. Sci. Sport. Exerc."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1590\/S0036-36341998000200005","article-title":"Validity and reproducibility of a food frequency questionnaire to assess dietary intake of women living in Mexico City","volume":"40","author":"Romieu","year":"1998","journal-title":"Salud Publica Mexico"},{"key":"ref_28","unstructured":"Hern\u00e1ndez-Avila, J., Gonz\u00e1lez-Avil\u00e9s, L., and Rosales-Mendoza, E. (2003). Manual de Usuario. SNUT Sistema de Evaluaci\u00f3n de H\u00e1bitos Nutricionales y Consumo de Nutrimentos, Instituto Nacional de Salud P\u00fablica. Response: Confirmed."},{"key":"ref_29","unstructured":"Lizaur, A.B.P., Laborde, L.M., and Gonz\u00e1lez, B.P. (2014). Sistema Mexicano de Alimentos Equivalentes, Fomento de Nutrici\u00f3n y Salud."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"608","DOI":"10.21149\/spm.v58i6.7842","article-title":"Relative validity of a food frequency questionnaire to identify dietary patterns in an adult Mexican population","volume":"58","author":"Tucker","year":"2016","journal-title":"Salud Publica Mexico"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Al Farizi, W.S., Hidayah, I., and Rizal, M.N. (2021, January 23\u201324). Isolation forest based anomaly detection: A systematic literature review. Proceedings of the 2021 8th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE), Semarang, Indonesia.","DOI":"10.1109\/ICITACEE53184.2021.9617498"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1093\/advances\/nmaa183","article-title":"Perspective: Big data and machine learning could help advance nutritional epidemiology","volume":"12","author":"Morgenstern","year":"2021","journal-title":"Adv. Nutr."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Russo, S., and Bonassi, S. (2022). Prospects and pitfalls of machine learning in nutritional epidemiology. Nutrients, 14.","DOI":"10.3390\/nu14091705"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1093\/ajcn\/nqaa113","article-title":"When two heads are better than one: Nutritional epidemiology meets machine learning","volume":"111","author":"Krishnan","year":"2020","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.ajcnut.2023.01.006","article-title":"Fructose consumption from different food sources and cardiometabolic biomarkers: Cross-sectional associations in US men and women","volume":"117","author":"Li","year":"2023","journal-title":"Am. J. Clin. Nutr."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"148427","DOI":"10.1016\/j.brainres.2023.148427","article-title":"Can early-life high fructose exposure induce long-term depression and anxiety-like behaviours?\u2013A preclinical systematic review","volume":"1814","author":"Andersen","year":"2023","journal-title":"Brain Res."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Coursan, A., Polve, D., Leroi, A.M., Monnoye, M., Roussin, L., Tavolacci, M.P., Quillard Muraine, M., Maccarone, M., Guerin, O., and Houivet, E. (2025). Fructose malabsorption induces dysbiosis and increases anxiety in Human and animal models. bioRxiv.","DOI":"10.1101\/2025.03.25.645339"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zhang, P., Sun, H., Cheng, X., Li, Y., Zhao, Y., Mei, W., Wei, X., Zhou, H., Du, Y., and Zeng, C. (2022). Dietary intake of fructose increases purine de novo synthesis: A crucial mechanism for hyperuricemia. Front. Nutr., 9.","DOI":"10.3389\/fnut.2022.1045805"},{"key":"ref_39","first-page":"766","article-title":"High dietary protein decreases fat deposition induced by high-fat and high-sucrose diet in rats","volume":"26","author":"Chaumontet","year":"2015","journal-title":"J. Nutr. Biochem."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.1007\/s00125-019-4956-4","article-title":"A carbohydrate-reduced high-protein diet improves HbA 1c and liver fat content in weight stable participants with type 2 diabetes: A randomised controlled trial","volume":"62","author":"Skytte","year":"2019","journal-title":"Diabetologia"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/s12937-016-0141-5","article-title":"Postprandial changes in cardiometabolic disease risk in young Chinese men following isocaloric high or low protein diets, stratified by either high or low meal frequency-a randomized controlled crossover trial","volume":"15","author":"Mok","year":"2015","journal-title":"Nutr. J."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.atherosclerosis.2021.05.011","article-title":"Is protein the forgotten ingredient: Effects of higher compared to lower protein diets on cardiometabolic risk factors. A systematic review and meta-analysis of randomised controlled trials","volume":"328","author":"Vogtschmidt","year":"2021","journal-title":"Atherosclerosis"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.sleh.2022.07.006","article-title":"Association between short sleep duration and intake of sugar and sugar-sweetened beverages: A systematic review and meta-analysis of observational studies","volume":"9","author":"Shahdadian","year":"2023","journal-title":"Sleep Health"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1007\/s11325-020-02155-5","article-title":"Association between sleep duration and sleep quality with sugar and sugar-sweetened beverages intake among university students","volume":"25","author":"Boozari","year":"2021","journal-title":"Sleep Breath."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"111254","DOI":"10.1016\/j.jfoodeng.2022.111254","article-title":"Application of ensemble neural-network method to integrated sugar content prediction model for citrus fruit using Vis\/NIR spectroscopy","volume":"338","author":"Kim","year":"2023","journal-title":"J. Food Eng."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"117412","DOI":"10.1016\/j.lwt.2025.117412","article-title":"Integrative hyperspectral imaging and artificial intelligence approaches for identifying sucrose substitutes and assessing cookie qualities","volume":"217","author":"Jeong","year":"2025","journal-title":"LWT"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1282","DOI":"10.1007\/s10620-016-4054-0","article-title":"Role of dietary fructose and hepatic de novo lipogenesis in fatty liver disease","volume":"61","author":"Softic","year":"2016","journal-title":"Dig. Dis. Sci."},{"key":"ref_48","first-page":"e220270","article-title":"Fructose drives de novo lipogenesis affecting metabolic health","volume":"257","author":"Gerber","year":"2023","journal-title":"J. Endocrinol."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.1038\/s42255-020-0261-2","article-title":"Fructose stimulated de novo lipogenesis is promoted by inflammation","volume":"2","author":"Todoric","year":"2020","journal-title":"Nat. Metab."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"3180","DOI":"10.1093\/jn\/nxab207","article-title":"FODMAP Consumption by Adults from the French Population-Based NutriNet-Sant\u00e9 Cohort","volume":"151","author":"Schneider","year":"2021","journal-title":"J. Nutr."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"022022","DOI":"10.1088\/1742-6596\/1168\/2\/022022","article-title":"An Overview of Overfitting and its Solutions","volume":"1168","author":"Ying","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"012100","DOI":"10.1088\/1742-6596\/1693\/1\/012100","article-title":"Research on Overfitting Problem and Correction in Machine Learning","volume":"1693","author":"Bu","year":"2020","journal-title":"J. Phys. Conf. Ser."}],"container-title":["Nutrients"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-6643\/17\/22\/3623\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:31:26Z","timestamp":1763645486000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-6643\/17\/22\/3623"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,20]]},"references-count":52,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["nu17223623"],"URL":"https:\/\/doi.org\/10.3390\/nu17223623","relation":{},"ISSN":["2072-6643"],"issn-type":[{"value":"2072-6643","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,20]]}}}