{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T19:35:38Z","timestamp":1793907338746,"version":"4.8.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T00:00:00Z","timestamp":1774483200000},"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. Endocrinol."],"abstract":"\n Background<\/jats:title>\n Although VAI, LAP, TyG and TyHGB are considered alternative indicators of abdominal fat deposition, their longitudinal association and strength of these indices with T2D remain unclear. The study aimed to evaluate the association between the indices and onset T2D in the elderly population across different FBG statuses and compare their predictive performance in risk assessment.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n Data were from the BaHLS, a cohort study of community-dwelling elderly individuals in Shenzhen, China. The study examined the associations between six novel obesity- and lipid-related indices (including BMI, WC, VAI, LAP, TyG and TyHGB) and the onset of T2D across different FBG statuses, including normal and elevated FBG. A multivariate\n Cox<\/jats:italic>\n proportional hazards model and a\n GAM<\/jats:italic>\n were employed to assess the longitudinal associations between each index and T2D.\n ROC<\/jats:italic>\n curves analysis and\n AUC<\/jats:italic>\n were utilized to evaluate the predictive performance of indices and determine their optimal cutoff values.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n A total of 18,251 participants were enrolled in the study, with 1,350 (7.40%) participants were diagnosed with T2D by end of 2022. In the overall elderly cohort, the adjusted\n HRs<\/jats:italic>\n of T2D per one-standard-deviation increase were: BMI 1.17 (95%\n CI<\/jats:italic>\n : 1.11\u20131.23), WC 1.23 (95%\n CI<\/jats:italic>\n : 1.16\u20131.30), VAI 1.30 (95%\n CI<\/jats:italic>\n : 1.24\u20131.37), LAP 1.21 (1.17\u20131.26), TyG 1.76 (95%\n CI<\/jats:italic>\n : 1.67\u20131.86), and TyHGB 1.37 (95%\n CI<\/jats:italic>\n : 1.33\u20131.42). Except for BMI and WC, the remaining indices were independent risk factors for the onset of T2D in both normal and elevated FBG individuals. These indices showed significant associations with T2D across different subgroups. Regarding predictive performance, all six indices demonstrated predictive ability for the onset of T2D across all participants (\n AUC<\/jats:italic>\n &gt; 0.5,\n P&lt;<\/jats:italic>\n 0.001). Specifically, TyG (\n AUC<\/jats:italic>\n =\u00a00.706, 95%\n CI<\/jats:italic>\n : 0.691\u20130.721) and TyHGB (\n AUC<\/jats:italic>\n \u00a0=\u00a00.737, 95%\n CI<\/jats:italic>\n : 0.724\u20130.750) exhibited better predictive performance than the other indices.\n RCS<\/jats:italic>\n analysis revealed that BMI and WC exhibited linear associations with the risk of T2D across all participants, whereas VAI, LAP, TyG, and TyHGB demonstrated nonlinear relationships.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n The study demonstrated that 6 obesity- and lipid- indices are positively associated with the incidence of onset T2D, and TyG and TyHGB demonstrated superior predictive performance for the onset of T2D in the elderly. Suggesting that TyG and TyHGB should be served as a valuable indicator for monitoring and preventing T2D.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fendo.2026.1798687","type":"journal-article","created":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T05:19:03Z","timestamp":1774502343000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Association between novel obesity- and lipid-related indices and diabetes across different FBG among elderly: a prospective cohort study"],"prefix":"10.3389","volume":"17","author":[{"given":"Xiang-yang","family":"He","sequence":"first","affiliation":[{"name":"Department of Health Management, Shenzhen Baoan District Chronic Diseases Prevent and Cure Hospital","place":["Shenzhen, Guangdong, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong-hui","family":"Ma","sequence":"additional","affiliation":[{"name":"Department of Endocrinology, The 987 Hospital of 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