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The Simple Method for Quantifying MetS (siMS) score offers potential for detecting cardiometabolic burden in younger and middle-aged, relatively healthy populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      We stratified 51 healthy adults (aged 18\u201360 years) into Low siMS (LMS, siMS\u2009&lt;\u20092.085,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200925) and High siMS (HMS, siMS\u2009\u2265\u20092.085,\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200926) groups based on the median siMS score and compared central hemodynamic parameters, heart rate variability (HRV), and microvascular function as independent predictors of cardiometabolic risk between these groups. Anthropometrics, body composition, hemodynamics (e.g., central blood pressure [BP], mean arterial pressure [MAP]), HRV (e.g., %R-R intervals\u2009&gt;\u200950 msec, pNN50; high-frequency power), microvascular reactivity (near-infrared spectroscopy vascular occlusion test), blood glucose and lipid profiles, and dietary intake were assessed using established protocols.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The HMS group exhibited significantly higher body mass, body mass index (BMI), waist and hip circumferences, fat mass, visceral fat, central and peripheral BP, MAP, and augmentation index adjusted to 75\u00a0bpm (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009\u2264\u20090.004), alongside lower HRV metrics (pNN50, high-frequency power, low-frequency power, and total power,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009\u2264\u20090.003), indicating increased cardiometabolic burden. No differences were observed in blood glucose, lipids, dietary intakes, or microvascular reactivity.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>These findings suggest that higher siMS scores reflect early cardiometabolic risk through adverse hemodynamic and autonomic profiles, even in the absence of overt MetS, metabolic abnormalities, or detectable microvascular dysfunction. The siMS score may serve as a proactive tool for identifying at-risk individuals, supporting targeted interventions to mitigate long-term cardiometabolic risk.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s40200-026-01870-2","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T04:32:39Z","timestamp":1771475559000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The simplified method for quantifying metabolic syndrome (siMS) score reflects an increased cardiometabolic burden: adiposity, hemodynamics, and HRV findings in young adults"],"prefix":"10.1007","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8925-997X","authenticated-orcid":false,"given":"Christopher J.","family":"Kotarsky","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jillian M.","family":"Lang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elena S.","family":"Shostak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William","family":"Quinn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valerie","family":"Chervinskaya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elisa","family":"Fioraso","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Everett","family":"Smith","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8160-9245","authenticated-orcid":false,"given":"Justin A.","family":"DeBlauw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer","family":"Lloyd","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7722-8818","authenticated-orcid":false,"given":"Stephen J.","family":"Ives","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,19]]},"reference":[{"key":"1870_CR1","doi-asserted-by":"publisher","first-page":"e047849","DOI":"10.1136\/bmjopen-2020-047849","volume":"11","author":"K Chee Cheong","year":"2021","unstructured":"Chee Cheong K, Lim KH, Ghazali SM, Teh CH, Cheah YK, Baharudin A, et al. 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