{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T11:33:52Z","timestamp":1791804832111,"version":"4.3.4"},"reference-count":51,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2025,11,24]],"date-time":"2025-11-24T00:00:00Z","timestamp":1763942400000},"content-version":"vor","delay-in-days":23,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Metabolism Res"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The aim of the study was to evaluate the association of Chinese visceral adiposity index (CVAI) with incident cardiovascular disease (CVD) and to compare it with traditional anthropometric indices in the Chinese population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 35,551 individuals without a history of CVD from Shanghai Suburban Adult Cohort and Biobank (SSACB) were enroled in this prospective cohort study. A Cox proportional hazard model with restricted cubic splines was used to evaluate the association between CVAI, body mass index (BMI), waist circumference (WC), waist\u2010hip ratio (WHR), waist\u2010height ratio (WHtR) and the risk of incident CVD, coronary heart disease (CHD) and stroke. Subgroup analysis was performed to estimate different associations across age, sex, hypertension, and diabetic groups. The area under the receiver operating characteristic (AUROC) curve, continuous net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to assess predictive performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      After adjusting for potential confounders, 1\u2010SD (standard deviation) increment of CVAI was associated with the highest elevated risk of incident CVD [HR (95% CI): 1.28 (1.21\u20131.37)], CHD [HR (95% CI):1.28 (1.17\u20131.40)] and stroke [HR (95% CI): 1.28 (1.17\u20131.40)] among all indices. Subgroup analyses suggested different associations across age and diabetic groups. According to ROC analysis, the AUC of CVAI for predicting CVD was significantly higher than BMI and WC in a general population, and additionally higher than WHR in females (\n                      <jats:italic>p<\/jats:italic>\n                      \u00a0&lt;\u00a00.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In comparison to traditional anthropometric indices, CVAI was more strongly and consistently associated with the risk of incident CVD and demonstrated promising potential in predicting CVD events, particularly among females.<\/jats:p>\n                  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