{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T06:30:33Z","timestamp":1785306633143,"version":"3.55.0"},"reference-count":42,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:00:00Z","timestamp":1781568000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>Background: Cardiometabolic diseases are shaped by complex interactions between biological and social determinants. While socioeconomic inequalities in cardiometabolic risk are well established, less is known about how these inequalities are distributed across multidimensional cardiometabolic phenotypes and whether they differ by sex. Objective: We aimed to examine sex differences in the socioeconomic gradient of cardiometabolic phenotypes using latent class analysis in a working-age population. Methods: A cross-sectional study was conducted in 3108 adults aged 18\u201365 years undergoing occupational health assessments in the Balearic Islands (Spain). Educational level was used as an indicator of socioeconomic position. Cardiometabolic risk was assessed using obesity, insulin resistance (METS-IR), metabolic dysfunction-associated steatotic liver disease (FLI), atherogenic index of plasma, and metabolic syndrome. Latent class analysis was applied to identify cardiometabolic phenotypes. Multinomial logistic regression models stratified by sex and interaction analyses were used to assess associations between educational level and class membership. Tests for linear trend and predicted probabilities were also estimated. Results: Four cardiometabolic phenotypes were identified: low-risk (40.8%), obesity-dominant (24.1%), dysmetabolic (19.3%), and high-risk multimorbid (15.8%). A clear socioeconomic gradient was observed, with lower educational attainment associated with a higher likelihood of belonging to adverse cardiometabolic profiles. This gradient was stronger among women. For the high-risk multimorbid class, the relative risk ratio comparing low vs. high educational level was 1.82 (95% CI 1.34\u20132.46) in men and 2.47 (95% CI 1.68\u20133.64) in women (p for interaction = 0.012). A significant linear trend across educational levels was observed in both sexes (p for trend &lt; 0.001). Predicted probabilities further confirmed a steeper increase in high-risk profiles among women with lower educational attainment. Conclusions: Cardiometabolic risk is structured into distinct phenotypic profiles that are socially patterned. Socioeconomic inequalities are strongly associated with adverse cardiometabolic phenotypes, with a more pronounced gradient among women. These findings highlight the need for gender-sensitive strategies addressing social determinants to reduce cardiometabolic health inequalities.<\/jats:p>","DOI":"10.3390\/metabo16060422","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T09:06:52Z","timestamp":1781600812000},"page":"422","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Sex Differences in the Socioeconomic Gradient of Latent Cardiometabolic Phenotypes in a Working-Age Population from the Balearic Islands (Spain): A Population-Based Analysis"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3071-5897","authenticated-orcid":false,"given":"Mar\u00eda Te\u00f3fila","family":"Vicente-Herrero","sequence":"first","affiliation":[{"name":"University of the Balearic Islands, 07009 Palma, Balearic Islands, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5222-5784","authenticated-orcid":false,"given":"Pedro J.","family":"T\u00e1rraga L\u00f3pez","sequence":"additional","affiliation":[{"name":"Faculty of Medicine, University of Castilla La Mancha, 02008 Albacete, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9367-2137","authenticated-orcid":false,"given":"Carla","family":"Busquets-Cort\u00e9s","sequence":"additional","affiliation":[{"name":"University of the Balearic Islands, 07009 Palma, Balearic Islands, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3848-687X","authenticated-orcid":false,"given":"Lluis","family":"Rodas Ca\u00f1ellas","sequence":"additional","affiliation":[{"name":"University of the Balearic Islands, 07009 Palma, Balearic Islands, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7439-8117","authenticated-orcid":false,"given":"\u00c1ngel Arturo","family":"L\u00f3pez Gonz\u00e1lez","sequence":"additional","affiliation":[{"name":"University of the Balearic Islands, 07009 Palma, Balearic Islands, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6887-4562","authenticated-orcid":false,"given":"Jos\u00e9 Ignacio","family":"Ram\u00edrez-Manent","sequence":"additional","affiliation":[{"name":"University of the Balearic Islands, 07009 Palma, Balearic Islands, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1186\/s13098-023-01025-w","article-title":"Metabolic health and adiposity transitions and risks of type 2 diabetes and cardiovascular diseases: A systematic review and meta-analysis","volume":"15","author":"Zhang","year":"2023","journal-title":"Diabetol. Metab. Syndr."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Mukherjee, M., Mukherjee, S., Thokala, H.R., and Ali, R.H. (2025). Classifying complex multimorbidity using latent class analysis and machine learning to generate insights into clustering of mental and cardiometabolic conditions. PLoS ONE, 20.","DOI":"10.1371\/journal.pone.0335676"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"102646","DOI":"10.1016\/j.jacadv.2026.102646","article-title":"Associations of Socioeconomic Status With Cardiorenal Metabolic Multimorbidity: Evidence From the UK Biobank Cohort","volume":"5","author":"Guo","year":"2026","journal-title":"JACC Adv."},{"key":"ref_4","first-page":"99","article-title":"Influence of sociodemographic variables and healthy habits on the values of type 2 diabetes risk scales","volume":"39","author":"Paublini","year":"2024","journal-title":"Acad. J. Health Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"118634","DOI":"10.1016\/j.socscimed.2025.118634","article-title":"The socioeconomic trajectories followed during early adulthood contribute to inequalities in cardiometabolic health by age 24 years","volume":"385","author":"Winpenny","year":"2025","journal-title":"Soc. Sci. Med."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Abreu, T.C., Beulens, J.W.J., Vaartjes, I., and Mackenbach, J.D. (2025). Life course socioeconomic trajectories and chronic disease risk in later life among 30,055 older adults across 27 European countries (the SHARE study). BMC Med., 24.","DOI":"10.1186\/s12916-025-04544-7"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"25736","DOI":"10.1038\/s41598-024-73997-2","article-title":"Cardiometabolic risk factor clusters in older adults using latent class analysis on the Bushehr elderly health program","volume":"14","author":"Afrashteh","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"de Faria, F.R., Miranda, V.P.N., Howe, C., Sasaki, J.E., Amato, A., Musumeci, G., and Amorim, P.R.D.S. (2025). Cardiometabolic Disease Risk Factors and Lifestyle Behaviors Among Adolescents: A Latent Class Analysis. Healthcare, 13.","DOI":"10.3390\/healthcare13080925"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Roomaney, R.A., van Wyk, B., Cois, A., and Pillay van-Wyk, V. (2023). Multimorbidity patterns in South Africa: A latent class analysis. Front. Public Health, 10.","DOI":"10.3389\/fpubh.2022.1082587"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"26","DOI":"10.4103\/ijabmr.ijabmr_314_25","article-title":"Sex-Specific Cardiometabolic Phenotypes of Metabolic Syndrome Identified by Latent Class Analysis in Indian Adults","volume":"16","author":"Sheth","year":"2026","journal-title":"Int. J. Appl. Basic. Med. Res."},{"key":"ref_11","first-page":"9","article-title":"Association between atherogenic dyslipidemia and lipid triad with cardiovascular risk scales in 418.343 Spanish workers","volume":"39","author":"Paublini","year":"2024","journal-title":"Acad. J. Health Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"25","DOI":"10.5334\/gh.1408","article-title":"Cardiometabolic Risk Clusters and Their Reproductive Correlates: A Latent Class Analysis of Indian Women","volume":"20","author":"Quarpong","year":"2025","journal-title":"Glob. Heart"},{"key":"ref_13","first-page":"59","article-title":"Prevalencia de factores de riesgo cardiometab\u00f3lico. Comparativa sector Comercio vs. Industria y variables asociadas","volume":"39","year":"2024","journal-title":"Acad. J. Health Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"126316","DOI":"10.1016\/j.envpol.2025.126316","article-title":"Inequalities in residential green space and trajectory of cardiometabolic multimorbidity: Different associations by sex and socioeconomic status","volume":"375","author":"Yang","year":"2025","journal-title":"Environ. Pollut."},{"key":"ref_15","first-page":"113","article-title":"Determination of cardiometabolic risk scales in 7.962 hotel receptionists","volume":"39","author":"Manzanero","year":"2024","journal-title":"Acad. J. Health Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e038708","DOI":"10.1161\/JAHA.124.038708","article-title":"Sex Differences in the Relationship of Socioeconomic Position With Cardiovascular Disease, Cardiovascular Risk Factors, and Estimated Cardiovascular Disease Risk: Results of the German National Cohort","volume":"14","author":"Peters","year":"2025","journal-title":"J. Am. Heart Assoc."},{"key":"ref_17","first-page":"50","article-title":"Gender Differences in the Association Between Socioeconomic Status and Cardiometabolic Health: National Health and Nutrition Examination Survey","volume":"4","author":"Assari","year":"2025","journal-title":"Glob. J. Cardiovasc. Dis."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"GBD 2021 US Burden of Disease Collaborators (2024). The burden of diseases, injuries, and risk factors by state in the USA, 1990\u20132021: A systematic analysis for the Global Burden of Disease Study 2021. Lancet, 404, 2314\u20132340. Erratum in Lancet 2025, 405, 302. https:\/\/doi.org\/10.1016\/S0140-6736(25)00105-9.","DOI":"10.1016\/S0140-6736(25)00105-9"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Xue, Q., Zhang, S., Yang, X., Zhang, Y.B., Dong, Y., Li, F., Li, S., Wu, N., Yan, T., and Wen, Y. (2025). Multimorbidity patterns and premature mortality in a prospective cohort: Effect modifications by socioeconomic status and healthy lifestyles. BMC Public Health, 25.","DOI":"10.1186\/s12889-025-22216-2"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"102420","DOI":"10.1016\/j.arr.2024.102420","article-title":"Frailty and socioeconomic position: A systematic review of observational studies","volume":"100","author":"Hanlon","year":"2024","journal-title":"Ageing Res. Rev."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1016\/S2213-8587(23)00086-4","article-title":"Metabolic health and cardiometabolic risk clusters: Implications for prediction, prevention, and treatment","volume":"11","author":"Stefan","year":"2023","journal-title":"Lancet Diabetes Endocrinol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Qiu, M., Paganin, S., Ohn, I., and Lin, L. (2025). Bayesian nonparametric latent class analysis with different item types. Psychol. Methods.","DOI":"10.1037\/met0000728"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lund, L., and Ritz, C. (2025). Flexible and modular latent transition analysis-A tutorial using R. PLoS ONE, 20.","DOI":"10.1371\/journal.pone.0317617"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"\u00c1lvarez-G\u00e1lvez, J., Ortega-Mart\u00edn, E., Carretero-Bravo, J., P\u00e9rez-Mu\u00f1oz, C., Su\u00e1rez-Lled\u00f3, V., and Ramos-Fiol, B. (2023). Social determinants of multimorbidity patterns: A systematic review. Front. Public Health, 11.","DOI":"10.3389\/fpubh.2023.1081518"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ahmadabad, A.D., Jahangiry, L., Gilani, N., Farhangi, M.A., Mohammadi, E., and Ponnet, K. (2024). Lifestyle patterns, nutritional, and metabolic syndrome determinants in a sample of the older Iranian population. BMC Geriatr., 24.","DOI":"10.1186\/s12877-024-04659-1"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"8255","DOI":"10.1038\/s41598-026-42858-5","article-title":"A latent class analysis of cardiometabolic risk factors and the predicted prevalence of subclinical atherosclerosis in middle-aged Swedish adults","volume":"16","author":"Anindya","year":"2026","journal-title":"Sci. Rep."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"e53371","DOI":"10.2196\/53371","article-title":"Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System: Latent Class Analysis","volume":"10","author":"Howell","year":"2024","journal-title":"JMIR Public Health Surveill."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1016\/S0140-6736(16)32380-7","article-title":"Socioeconomic status and the 25 \u00d7 25 risk factors as determinants of premature mortality: A multicohort study and meta-analysis of 1\u00b77 million men and women","volume":"389","author":"Stringhini","year":"2017","journal-title":"Lancet"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Barakat, C., and Konstantinidis, T. (2023). A Review of the Relationship between Socioeconomic Status Change and Health. Int. J. Environ. Res. Public Health, 20.","DOI":"10.3390\/ijerph20136249"},{"key":"ref_30","first-page":"27","article-title":"Influence of sociodemographic variables and healthy habits on the values of overweight and obesity scales in 386,924 Spanish workers","volume":"39","author":"Paublini","year":"2024","journal-title":"Acad. J. Health Sci."},{"key":"ref_31","unstructured":"GBD 2023 Disease and Injury and Risk Factor Collaborators (2025). Burden of 375 diseases and injuries, risk-attributable burden of 88 risk factors, and healthy life expectancy in 204 countries and territories, including 660 subnational locations, 1990\u20132023: A systematic analysis for the Global Burden of Disease Study 2023. Lancet, 406, 1873\u20131922."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhou, L., Nutakor, J.A., Larnyo, E., Addai-Dansoh, S., Cui, Y., Gavu, A.K., and Kissi, J. (2024). Exploring socioeconomic status, lifestyle factors, and cardiometabolic disease outcomes in the United States: Insights from a population-based cross-sectional study. BMC Public Health, 24.","DOI":"10.1186\/s12889-024-19685-2"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Gilardini, L., Croci, M., Cavaggioni, L., Pasqualinotto, L., and Bertoli, S. (2024). Sex differences in cardiometabolic risk factors and in response to lifestyle intervention in prepubertal and pubertal subjects with obesity. Front. Pediatr., 12.","DOI":"10.3389\/fped.2024.1304451"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1007\/s00125-019-05040-3","article-title":"Sex differences in metabolic regulation and diabetes susceptibility","volume":"63","author":"Tramunt","year":"2020","journal-title":"Diabetologia"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"688","DOI":"10.1038\/s41574-023-00906-4","article-title":"Sex differences in cardiometabolic health","volume":"19","author":"Dar","year":"2023","journal-title":"Nat. Rev. Endocrinol."},{"key":"ref_36","unstructured":"(2026, May 02). Geneva: World Health Organization. Available online: https:\/\/www.who.int\/news-room\/questions-and-answers\/item\/gender-and-health."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1161\/CIRCULATIONAHA.117.028595","article-title":"Gender\/Sex as a Social Determinant of Cardiovascular Risk","volume":"137","author":"Scovelle","year":"2018","journal-title":"Circulation"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"101272","DOI":"10.1016\/j.ssmph.2022.101272","article-title":"Women carry the weight of deprivation on physical inactivity: Moderated mediation analyses in a European sample of adults over 50 Years of age","volume":"20","author":"Maltagliati","year":"2022","journal-title":"SSM Popul. Health"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1136\/jech-2025-224476","article-title":"Does lifestyle explain the relationship between socioeconomic position and multimorbidity of cancer and cardiometabolic diseases? A mediation analysis applied to the European Prospective Investigation into Cancer and Nutrition","volume":"80","author":"Manfredi","year":"2025","journal-title":"J. Epidemiol. Community Health"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"m693","DOI":"10.1136\/bmj.m693","article-title":"Health equity in England: The Marmot review 10 years on","volume":"368","author":"Marmot","year":"2020","journal-title":"BMJ"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"118542","DOI":"10.1016\/j.socscimed.2025.118542","article-title":"Socioeconomic inequalities in developing cardiometabolic diseases and transition to depression: A trajectory analysis of large-scale population-based study","volume":"384","author":"Chen","year":"2025","journal-title":"Soc. Sci. Med."},{"key":"ref_42","first-page":"107","article-title":"Association between sociodemographic variables, healthy habits and stress with insulin resistance risk scales","volume":"40","year":"2025","journal-title":"Acad. J. Health Sci."}],"container-title":["Metabolites"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-1989\/16\/6\/422\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T10:31:45Z","timestamp":1781605905000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-1989\/16\/6\/422"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,16]]},"references-count":42,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["metabo16060422"],"URL":"https:\/\/doi.org\/10.3390\/metabo16060422","relation":{},"ISSN":["2218-1989"],"issn-type":[{"value":"2218-1989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,16]]}}}