{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T06:40:45Z","timestamp":1772692845331,"version":"3.50.1"},"reference-count":24,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Cardiovasc. Med."],"abstract":"\n The association between metabolic syndrome (MetS) and its components with cardiovascular disease (CVD) incidence represents a key global public health focus. However, given the unique dietary patterns of the population in southern Xinjiang, China, the differential effects of various Mets components on CVD onset and the interactions among these components remain poorly elucidated. This retrospective cohort study was conducted from 2018 to 2023, enrolling 144,966 participants from a county in southern Xinjiang with a median follow-up duration of 5.0 years. Cox proportional hazards regression and interaction analysis were applied to systematically explore the dose-response relationship between the number of abnormal values of the five core Mets indicators and CVD incidence. Among the 144,966 participants with no baseline CVD, the prevalence of Mets was 14.8%; Mets patients had a significantly higher mean age [(50.96\n \n \n \u00b1<\/mml:mo>\n <\/mml:math>\n <\/jats:inline-formula>\n 13.28) vs. (40.30\n \n \n \u00b1<\/mml:mo>\n <\/mml:math>\n <\/jats:inline-formula>\n 15.94) years,\n \n \n P<\/mml:mi>\n <<\/mml:mo>\n 0.001<\/mml:mn>\n <\/mml:math>\n <\/jats:inline-formula>\n ]. During a median follow-up of 5.0 years, the incidence of CVD was 5.13% (51.3 cases\/1,000 person-years) in the Mets group and 2.18% in the non-Mets group. After adjusting for confounders, elevated waist circumference (adjusted hazard ratio(aHR) = 1.12, 95%CI:1.08\u20131.15,\n \n \n P<\/mml:mi>\n <<\/mml:mo>\n 0.001<\/mml:mn>\n <\/mml:math>\n <\/jats:inline-formula>\n ), elevated blood pressure (aHR = 1.24, 95%CI:1.20\u20131.29,\n \n \n P<\/mml:mi>\n <<\/mml:mo>\n 0.001<\/mml:mn>\n <\/mml:math>\n <\/jats:inline-formula>\n ), and high blood glucose (aHR = 1.14, 95%CI:1.10\u20131.18,\n \n \n P<\/mml:mi>\n <<\/mml:mo>\n 0.001<\/mml:mn>\n <\/mml:math>\n <\/jats:inline-formula>\n ) were independently associated with increased incident CVD events, while elevated triglycerides (aHR = 1.03, 95%CI:1.00\u20131.07,\n \n \n P<\/mml:mi>\n =<\/mml:mo>\n 0.065<\/mml:mn>\n <\/mml:math>\n <\/jats:inline-formula>\n ) and low high-density lipoprotein cholesterol (aHR = 1.00, 95%CI:0.97\u20131.03,\n \n \n P<\/mml:mi>\n =<\/mml:mo>\n 0.8788<\/mml:mn>\n <\/mml:math>\n <\/jats:inline-formula>\n ) showed no significant effect. Incident CVD events increased progressively with the number of abnormal Mets components (aHR = 1.22\u20132.72,\n \n \n P<\/mml:mi>\n <\/mml:math>\n <\/jats:inline-formula>\n for trend &lt;0.001). Significant positive additive interaction was observed between waist circumference and blood pressure, but not between other component pairs. These findings underscore the value of integrated waist circumference and blood pressure management for CVD prevention in similar populations, though recall bias and limited causal inference exist due to the retrospective design.\n <\/jats:p>","DOI":"10.3389\/fcvm.2026.1727588","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T05:25:48Z","timestamp":1772688348000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A cohort study in Southern Xinjiang, China, 2018\u20132023 on the association of metabolic syndrome components and their interactions with cardiovascular disease risk"],"prefix":"10.3389","volume":"13","author":[{"given":"Sijing","family":"Wang","sequence":"first","affiliation":[{"name":"School of Traditional Chinese Medicine, Xinjiang Medical University","place":["Urumqi, 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Telecommunications","place":["Beijing, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingkai","family":"Mao","sequence":"additional","affiliation":[{"name":"Institute of Medical Engineering Interdisciplinary Research, Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongqing","family":"An","sequence":"additional","affiliation":[{"name":"The Fourth Affiliated Hospital of Xinjiang Medical University, Xinjiang Medical University","place":["Urumqi, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Medical Engineering Interdisciplinary Research, Xinjiang Medical University","place":["Urumqi, China"]},{"name":"School of Computer Science and Technology, Xinjiang University","place":["Urumqi, 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