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The combined impact of TyG-Frailty Index (TyGFI) has not been adequately explored. This study aimed to investigate the association between TyGFI and the risk of cardiovascular disease (CVD) and stroke.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 5448 participants from the China Health and Retirement Longitudinal Study (CHARLS) and 1139 participants from the U.S. National Health and Nutrition Examination Survey (NHANES) were included. Multivariable logistic regression models were used to estimate associations with CVD and stroke, adjusting for demographic, clinical, and lifestyle covariates. Restricted cubic spline (RCS) and subgroup analyses were employed to examine dose\u2013response relationships and interaction effects.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Higher TyGFI levels were associated with older age, adverse metabolic parameters, and increased prevalence of hypertension, diabetes, and dyslipidemia. In fully adjusted models, the highest TyGFI quartile was significantly associated with increased risks of CVD (CHARLS: OR 15.09, 95% CI 9.65\u201323.60; NHANES: OR 4.98, 95% CI 2.04\u201312.19) and stroke (CHARLS: OR 21.12, 95% CI 6.44\u201369.23; NHANES: OR 12.98, 95% CI 2.58\u201365.17), with consistent dose\u2013response trends confirmed by RCS analyses. Subgroup analyses further demonstrated the robustness of these associations across diverse demographic and clinical strata.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>TyGFI is a strong and independent predictor of CVD and stroke in two nationally representative cohorts. By integrating metabolic and functional risk dimensions, TyGFI provides a more comprehensive risk stratification tool, with significant implications for early identification and prevention of cardiovascular events in aging populations.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12933-025-02880-9","type":"journal-article","created":{"date-parts":[[2025,8,4]],"date-time":"2025-08-04T16:22:23Z","timestamp":1754324543000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["Predictive value of the combined triglyceride-glucose and frailty index for cardiovascular disease and stroke in two prospective cohorts"],"prefix":"10.1186","volume":"24","author":[{"given":"Yi-Chang","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shi-Qi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia-Kai","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi-Hua","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bi-Kui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rao","family":"Fu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miao","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,4]]},"reference":[{"issue":"10292","key":"2880_CR1","doi-asserted-by":"publisher","first-page":"2385","DOI":"10.1016\/s0140-6736(21)00684-x","volume":"397","author":"B Vogel","year":"2021","unstructured":"Vogel B, Acevedo M, Appelman Y, et al. 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