{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T06:04:25Z","timestamp":1780985065660,"version":"3.54.1"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T00:00:00Z","timestamp":1780963200000},"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. Nutr."],"abstract":"\n Objective<\/jats:title>\n This study aimed to systematically evaluate the association of triglyceride-glucose body mass index (TyG-BMI) with the risk of gestational diabetes mellitus (GDM).<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n A systematic search was conducted in PubMed, Embase, Web of Science, the Cochrane Library, China National Knowledge Infrastructure, Wanfang Data, and Chinese Science and Technology Journal Database from inception to 31 March 2026 for cohort studies investigating the association between TyG-BMI and GDM risk. Two reviewers independently conducted literature screening, data extraction and study quality assessment using the Newcastle-Ottawa Scale (NOS). Meta-analysis was performed with Stata 16.0 for heterogeneity test, sensitivity analysis and publication bias assessment, and Review Manager 5.4.1 for effect size pooling and subgroup analyses. Heterogeneity across studies was assessed using the Cochrane Q-test and\n I<\/jats:italic>\n 2<\/jats:sup>\n statistic. A fixed-effects model was used for effect size pooling if heterogeneity was low (\n P<\/jats:italic>\n &gt; 0.1,\n I<\/jats:italic>\n 2<\/jats:sup>\n \u2264 40%); a random-effects model was adopted for significant heterogeneity (\n P<\/jats:italic>\n &lt; 0.1,\n I<\/jats:italic>\n 2<\/jats:sup>\n \u2265 50%). Subgroup analyses were stratified by study design, maternal age and sample size to explore heterogeneity sources. Sensitivity analyses were performed to examine result stability, and publication bias was assessed by funnel plot and Egger's regression test.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n This meta-analysis included a total of 6 cohort studies with 52,877 participants. The overall pooled OR was 2.13 (95% CI: 1.26\u20133.61,\n P<\/jats:italic>\n = 0.005,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 97%). Subgroup analyses showed significant positive associations in prospective cohorts (OR = 2.55, 95% CI: 1.82\u20133.58,\n P<\/jats:italic>\n &lt; 0.0001,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 49%), women aged \u2264 32 years (OR = 2.12, 95% CI: 1.53\u20132.95,\n P<\/jats:italic>\n &lt; 0.0001,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 45%), and large-sample studies (\u22651,000 participants, OR = 2.39, 95% CI: 1.77\u20133.22,\n P<\/jats:italic>\n &lt; 0.0001,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 70%). A marginally significant association was found in retrospective cohorts (OR = 1.78, 95% CI: 1.00\u20133.17,\n P<\/jats:italic>\n = 0.05,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 91%), whereas no significant associations were identified in women aged &gt;32 years (OR = 2.08, 95% CI: 0.89\u20134.83,\n P<\/jats:italic>\n = 0.09,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 99%) or small-sample studies (&lt;1,000 participants, OR = 1.68, 95% CI: 0.54\u20135.22,\n P<\/jats:italic>\n = 0.37,\n I<\/jats:italic>\n 2<\/jats:sup>\n = 69%). No significant between-subgroup differences were observed across all analyses. Sensitivity analyses indicated stable results, with\n I<\/jats:italic>\n 2<\/jats:sup>\n reduced from 97% to 60% following the exclusion of one study. Funnel plot and statistical tests showed no significant publication bias; however, these assessments have limited reliability when fewer than 10 studies are included and should be interpreted with caution.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n This exploratory meta-analysis suggests that increased early-pregnancy TyG-BMI was significantly associated with a higher risk of GDM. TyG-BMI may serve as a potential early predictive biomarker for GDM, although further large-scale prospective studies are warranted to validate these results and identify potential effect modifiers.<\/jats:p>\n <\/jats:sec>\n \n Systematic review registration<\/jats:title>\n \n https:\/\/www.crd.york.ac.uk\/PROSPERO\/view\/CRD420261291099<\/jats:ext-link>\n , identifier: CRD420261291099.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fnut.2026.1833116","type":"journal-article","created":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T05:44:13Z","timestamp":1780983853000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The triglyceride glucose-body mass index and the risk of gestational diabetes mellitus: a systematic review and meta-analysis"],"prefix":"10.3389","volume":"13","author":[{"given":"Jian","family":"Sun","sequence":"first","affiliation":[{"name":"Changchun University of Chinese 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