{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T06:03:24Z","timestamp":1771567404506,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T00:00:00Z","timestamp":1771372800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background\/Objectives: Current evidence on the diabetes prevention benefit of substituting red meat with white meat remains inconsistent and is predominantly based on Western populations. This research examined whether the benefits of such dietary substitution depend on habitual red meat intake levels. Methods: This prospective analysis included 12,143 adults from the China Health and Nutrition Survey (2004\u20132015). Dietary intake was assessed by multiple 24 h recalls supplemented by a household food inventory. Incident diabetes was identified via self-report and supplementary biochemical data. Estimates of hazard ratios (HRs) and 95% confidence intervals (CIs) were obtained through Cox proportional hazards modeling. Dose\u2013response relationships were examined using restricted cubic splines. Substitution effects were evaluated within strata defined by baseline red meat intake (&lt;75 vs. \u226575 g\/day). Results: During 83,046 person-years of follow-up, 687 incident diabetes cases occurred. U-shaped associations were identified for both red meat (lowest risk at 75 g\/day) and white meat (lowest risk at 60 g\/day) consumption in relation to diabetes risk (p-nonlinearity &lt; 0.0001). Substitution was not associated with diabetes risk in the low-intake stratum (&lt;75 g\/day, p = 0.107). Conversely, in the high-intake stratum (\u226575 g\/day), replacing 50 g\/day of red meat with white meat was associated with a 34% lower diabetes risk (HR: 0.66; 95% CI: 0.51, 0.86; p = 0.002). Conclusions: Meat intake shows a nonlinear association with diabetes risk in Chinese adults. The potential benefit of substituting white meat for red meat is conditional, with a more pronounced effect observed among individuals with high habitual red meat consumption, which may support the development of targeted dietary guidance for this subgroup.<\/jats:p>","DOI":"10.3390\/nu18040669","type":"journal-article","created":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T12:59:16Z","timestamp":1771419556000},"page":"669","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Substitution of White Meat for Red Meat and Diabetes Risk: A Prospective Cohort Study Stratified by Red Meat Intake"],"prefix":"10.3390","volume":"18","author":[{"given":"Langrun","family":"Wang","sequence":"first","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Guo","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiran","family":"Guan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8631-2476","authenticated-orcid":false,"given":"Chao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ran","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Keji","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruixin","family":"Zhu","sequence":"additional","affiliation":[{"name":"Research Center for Probiotics, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2427-9064","authenticated-orcid":false,"given":"Jingjing","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Nutrition and Food Quality, Department of Nutrition and Health, China Agricultural University, Beijing 100193, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/S2213-8587(25)00299-2","article-title":"11th edition of the IDF Diabetes Atlas: Global, regional, and national diabetes prevalence estimates for 2024 and projections for 2050","volume":"14","author":"Genitsaridi","year":"2026","journal-title":"Lancet Diabetes Endocrinol."},{"key":"ref_2","first-page":"28","article-title":"The national and provincial prevalence and non-fatal burdens of diabetes in China from 2005 to 2023 with projections of prevalence to 2050","volume":"12","author":"Zhou","year":"2025","journal-title":"Mil. 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