{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T14:11:04Z","timestamp":1792591864701,"version":"4.5.0"},"reference-count":27,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T00:00:00Z","timestamp":1746662400000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Int J of Rheum Dis"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Objective<\/jats:title><jats:p>This longitudinal study investigated age\u2010 and gender\u2010specific disparities in hyperuricemia and their metabolic associations in a community\u2010based cohort, addressing gaps in long\u2010term uric acid trajectory data.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A prospective cohort of 465 adults (123 males, 342 females) was stratified by serum uric acid (<jats:styled-content style=\"fixed-case\">SUA<\/jats:styled-content> &gt;\u2009420\u2009\u03bcmol\/L) and followed annually for 3\u2009years. Standardized assessments included anthropometric, biochemical, and clinical evaluations.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Males had a 3.8\u2010fold higher hyperuricemia prevalence than females (39.84% vs. 10.53%, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001), with age\u2010specific peaks in males (20\u201329 and &gt;\u200960\u2009years) and females (&gt;\u200960\u2009years). Hyperuricemic individuals exhibited elevated <jats:styled-content style=\"fixed-case\">BMI<\/jats:styled-content> (24.75\u2009\u00b1\u20093.38 vs. 22.43\u2009\u00b1\u20093.01\u2009kg\/m<jats:sup>2<\/jats:sup>, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001), systolic blood pressure (<jats:styled-content style=\"fixed-case\">SBP<\/jats:styled-content>: 124.62\u2009\u00b1\u200916.42 vs. 118.25\u2009\u00b1\u200914.99\u2009<jats:styled-content style=\"fixed-case\">mmHg<\/jats:styled-content>, <jats:italic>p<\/jats:italic>\u2009=\u20090.001), fasting glucose (<jats:styled-content style=\"fixed-case\">FBG<\/jats:styled-content>: 5.48\u2009\u00b1\u20090.79 vs. 5.25\u2009\u00b1\u20090.80\u2009mmol\/L, <jats:italic>p<\/jats:italic>\u2009=\u20090.013), and renal dysfunction markers (serum creatinine: 74.10\u2009\u00b1\u200916.57 vs. 59.24\u2009\u00b1\u200914.68\u2009\u03bcmol\/L, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001). Age\u2010stratified comorbidity patterns showed dyslipidemia predominance in younger groups (58.82%) versus cardiorenal complications hypertension (31.03%), elevated <jats:styled-content style=\"fixed-case\">FBG<\/jats:styled-content> (41.38%) and renal impairment (75.86%) in older adults. Multivariate analysis identified age, sex, <jats:styled-content style=\"fixed-case\">BMI<\/jats:styled-content>, and lipid profiles as <jats:styled-content style=\"fixed-case\">SUA<\/jats:styled-content> determinants (<jats:italic>\u03b2<\/jats:italic>\u2009=\u2009\u22120.248 to 0.472, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05), with <jats:styled-content style=\"fixed-case\">eGFR<\/jats:styled-content> inversely associated (<jats:italic>\u03b2<\/jats:italic>\u2009=\u2009\u22120.273, <jats:italic>p<\/jats:italic>\u2009&lt;\u20090.05). Longitudinal data revealed alanine aminotransferase (<jats:styled-content style=\"fixed-case\">ALT<\/jats:styled-content>) as a novel predictor (<jats:italic>\u03b2<\/jats:italic>\u2009=\u20090.125, <jats:italic>p<\/jats:italic>\u2009=\u20090.038), while baseline hyperuricemia did not predict long\u2010term <jats:styled-content style=\"fixed-case\">SUA<\/jats:styled-content>.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Hyperuricemia demonstrates significant age\u2010 and gender\u2010related disparities, with persistent metabolic abnormalities contributing to cardiorenal and hepatic risks. Younger populations face dyslipidemia and liver dysfunction, whereas older adults exhibit hypertension and renal impairment. Regular monitoring and age\u2010specific interventions are critical for mitigating metabolic syndrome progression.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1756-185x.70254","type":"journal-article","created":{"date-parts":[[2025,5,8]],"date-time":"2025-05-08T07:36:32Z","timestamp":1746689792000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Age\u2010 and Gender\u2010Specific Dynamics of Hyperuricemia: A Longitudinal Community Study on Metabolic Trajectories and Comorbidity Stratification"],"prefix":"10.1111","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-9953-1315","authenticated-orcid":false,"given":"Xianghui","family":"Wen","sequence":"first","affiliation":[{"name":"Shenzhen Longhua District Central Hospital  Shenzhen China"},{"name":"Shenzhen Longhua Institute of Immunology Transformation  Shenzhen 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