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However, the association between TyG-BMI and pre-diabetes remains to be elucidated.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>More than 100,000 subjects with normal glucose at baseline received follow-up. The main outcome event of concern was pre-diabetes defined according to the diagnostic criteria recommended by the American Diabetes Association (ADA) in 2018 and the World Health Organization (WHO) in 1999. A Cox proportional hazard regression model was used to evaluate the role of TyG-BMI in identifying people at high risk of pre-diabetes.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>At a mean observation period of 3.1\u2009years, the incidence of pre-diabetes in the cohort was 3.70 and 12.31% according to the WHO and ADA diagnostic criteria for pre-diabetes, respectively. The multivariate Cox regression analysis demonstrated that TyG-BMI was independently positively correlated with pre-diabetes, and there was a special population dependence phenomenon. Among them, non-obese people, women and people under 50\u2009years old had a significantly higher risk of TyG-BMI-related pre-diabetes (<jats:italic>P<\/jats:italic>-interaction&lt;\u20090.05).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>These findings suggest that a higher TyG-BMI significantly increases an individual\u2019s risk of pre-diabetes, and this risk is significantly higher in women, non-obese individuals, and individuals younger than 50\u2009years of age.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12944-021-01594-7","type":"journal-article","created":{"date-parts":[[2021,11,14]],"date-time":"2021-11-14T01:02:23Z","timestamp":1636851743000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":70,"title":["Triglyceride glucose-body mass index in identifying high-risk groups of pre-diabetes"],"prefix":"10.1186","volume":"20","author":[{"given":"Chunyuan","family":"Jiang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruijuan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maobin","family":"Kuang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingchun","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9373-928X","authenticated-orcid":false,"given":"Yang","family":"Zou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,11,14]]},"reference":[{"issue":"9833","key":"1594_CR1","doi-asserted-by":"publisher","first-page":"2279","DOI":"10.1016\/S0140-6736(12)60283-9","volume":"379","author":"AG Tab\u00e1k","year":"2012","unstructured":"Tab\u00e1k AG, Herder C, Rathmann W, Brunner EJ, Kivim\u00e4ki M. 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