{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T09:36:35Z","timestamp":1788687395723,"version":"build-2803163510"},"reference-count":46,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T00:00:00Z","timestamp":1681776000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Financial Projects: Assessment and Application of Nutrients Requirement and Food Environment for Chinese Residents","award":["131031107000210003"],"award-info":[{"award-number":["131031107000210003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>High iron stores have been reported to be associated with type 2 diabetes mellitus (T2DM). However, evidence for the associations of iron metabolism with T2DM is inconsistent, and whether there is a threshold effect remains controversial. In the present study, we aimed to examine the associations between various iron biomarkers and the risk of T2DM as well as impaired glucose metabolism (IGM) and hyperglycemia in Chinese women of childbearing age. A total of 1145 women were divided into three groups (normal blood glucose metabolism group; IGM group; T2DM group). Biomarkers of iron metabolism (serum ferritin (SF), transferrin, soluble transferrin receptor (sTfR), transferrin saturation, serum iron, total body iron, and sTfR-to-lgferritin index) were measured. After adjusting for various confounding risk factors, SF and sTfR were positively associated with the risk of IGM (fourth vs. first quartile: SF odds ratio (OR) = 1.93 (95% CI 1.17\u20133.20) and sTfR OR = 3.08 (95% CI 1.84\u20135.14)) and T2DM (SF OR = 2.39 (95% CI 1.40\u20134.06) and sTfR OR = 3.84 (95% CI 2.53\u20135.83)). There was a nonlinear relationship between SF and risk of T2DM and hyperglycemia (p for nonlinearity &lt; 0.01). Our findings suggested that SF and sTfR could be independent predictors of T2DM risk.<\/jats:p>","DOI":"10.3390\/nu15081935","type":"journal-article","created":{"date-parts":[[2023,4,18]],"date-time":"2023-04-18T01:36:45Z","timestamp":1681781805000},"page":"1935","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Association of Body Iron Metabolism with Type 2 Diabetes Mellitus in Chinese Women of Childbearing Age: Results from the China Adult Chronic Disease and Nutrition Surveillance (2015)"],"prefix":"10.3390","volume":"15","author":[{"given":"Jie","family":"Feng","sequence":"first","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Committee, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyun","family":"Shan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Committee, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China"},{"name":"Hunan Key Laboratory of Typical Environmental Pollution and Health Hazards, School of Public Health, Hengyang Medical School, University of South China, Hengyang 241001, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Committee, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1939-5906","authenticated-orcid":false,"given":"Jiaxi","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Committee, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Cao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Committee, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lichen","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Trace Element Nutrition of National Health Committee, National Institute for Nutrition and Health, Chinese Center for Disease Control and Prevention, Beijing 100050, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107843","DOI":"10.1016\/j.diabres.2019.107843","article-title":"Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9(th) edition","volume":"157","author":"Saeedi","year":"2019","journal-title":"Diabetes Res. 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