{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T21:18:51Z","timestamp":1778879931470,"version":"3.51.4"},"reference-count":52,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T00:00:00Z","timestamp":1638489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation Program of China","award":["81973137"],"award-info":[{"award-number":["81973137"]}]},{"name":"National Natural Science Foundation Program of China","award":["82173608"],"award-info":[{"award-number":["82173608"]}]},{"name":"Hunan Provincial Key Research and Development Program","award":["2018SK2062"],"award-info":[{"award-number":["2018SK2062"]}]},{"name":"Fundamental Research Funds for the Central Universities of Central South University","award":["2020zzts238"],"award-info":[{"award-number":["2020zzts238"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>In order to explore the association between trajectories of body mass index (BMI) and mid-upper arm circumference (MUAC) and diabetes and to assess the effectiveness of the models to predict diabetes among Chinese prediabetic people, we conducted this study. Using a national longitudinal study, 1529 cases were involved for analyzing the association between diabetes and BMI trajectories or MUAC trajectories. Growth mixture modeling was conducted among the prediabetic Chinese population to explore the trajectories of BMI and MUAC, and logistic regression was applied to evaluate the association between these trajectories and the risk of diabetes. The receiver operating characteristic curve (ROC) and the area under the curve (AUC) were applied to assess the feasibility of prediction. BMI and MUAC were categorized into 4-class trajectories, respectively. Statistically significant associations were observed between diabetes in certain BMI and MUAC trajectories. The AUC for trajectories of BMI and MUAC to predict diabetes was 0.752 (95% CI: 0.690\u20130.814). A simple cross-validation using logistic regression indicated an acceptable efficiency of the prediction. Diabetes prevention programs should emphasize the significance of body weight control and maintaining skeletal muscle mass and resistance training should be recommended for prediabetes.<\/jats:p>","DOI":"10.3390\/nu13124356","type":"journal-article","created":{"date-parts":[[2021,12,6]],"date-time":"2021-12-06T03:10:38Z","timestamp":1638760238000},"page":"4356","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese"],"prefix":"10.3390","volume":"13","author":[{"given":"Fang","family":"Li","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China"},{"name":"Hunan Provincial Key Laboratory of Clinical Epidemiology, Changsha 410078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lizhang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China"},{"name":"Hunan Provincial Key Laboratory of Clinical Epidemiology, Changsha 410078, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"American Diabetes Association (2021). 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