{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:06:51Z","timestamp":1740146811406,"version":"3.37.3"},"reference-count":56,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T00:00:00Z","timestamp":1667779200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["093206\/Z\/10\/Z"],"award-info":[{"award-number":["093206\/Z\/10\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100019418","name":"NIHR Maudsley Biomedical Research Centre","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100019418","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100015091","name":"NIHR Collaboration for Leadership in Applied Health Research and Care South London","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100015091","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>Prevention of cardiovascular disease and diabetes is a priority in low- and middle-income countries, especially in South Asia where these are leading causes of morbidity and mortality. The metabolic syndrome is a tool to identify cardiometabolic risk, but the validity of the metabolic syndrome as a clinical construct is debated. This study tested the existence of the metabolic syndrome, explored alternative cardiometabolic risk characterisations, and examined genetic and environmental factors in a South Asian population sample.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>Data came from the Colombo Twin and Singleton follow-up Study, which recruited twins and singletons in Colombo, Sri Lanka, in 2012\u20132015 (<jats:italic>n<\/jats:italic> = 3476). Latent class analysis tested the clustering of metabolic syndrome indicators (waist circumference, high-density lipoprotein cholesterol, triglycerides, blood pressure, fasting plasma glucose, medications, and diabetes). Regression analyses tested cross-sectional associations between the identified latent cardiometabolic classes and sociodemographic covariates and health behaviours. Structural equation modelling estimated genetic and environmental contributions to cardiometabolic risk profiles. All analyses were stratified by sex (<jats:italic>n<\/jats:italic> = 1509 men, <jats:italic>n<\/jats:italic> = 1967 women).<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>Three classes were identified in men: 1) \u201cHealthy\u201d (52.3%), 2) \u201cCentral obesity, high triglycerides, high fasting plasma glucose\u201d (40.2%), and 3) \u201cCentral obesity, high triglycerides, diabetes\u201d (7.6%). Four classes were identified in women: 1) \u201cHealthy\u201d (53.2%), 2) \u201cVery high central obesity, low high-density lipoprotein cholesterol, raised fasting plasma glucose\u201d (32.8%), 3) \u201cVery high central obesity, diabetes\u201d (7.2%) and 4) \u201cCentral obesity, hypertension, raised fasting plasma glucose\u201d (6.8%). Older age in men and women, and high socioeconomic status in men, was associated with cardiometabolic risk classes, compared to the \u201cHealthy\u201d classes. In men, individual differences in cardiometabolic class membership were due to environmental effects. In women, genetic differences predicted class membership.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>The findings did not support the metabolic syndrome construct. Instead, distinct clinical profiles were identified for men and women, suggesting different aetiological pathways.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0276647","type":"journal-article","created":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T18:30:04Z","timestamp":1667845804000},"page":"e0276647","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["Cardiometabolic risk profiles in a Sri Lankan twin and singleton sample"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6464-4855","authenticated-orcid":true,"given":"Lisa","family":"Harber-Aschan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ioannis","family":"Bakolis","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicholas","family":"Glozier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khalida","family":"Ismail","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaushalya","family":"Jayaweera","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gayani","family":"Pannala","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carmine","family":"Pariante","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fruhling","family":"Rijsdijk","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sisira","family":"Siribaddana","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Athula","family":"Sumathipala","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Helena M. 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