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中国人中,体质变量轨迹与糖尿病风险之间的关联。

The Association between Trajectories of Anthropometric Variables and Risk of Diabetes among Prediabetic Chinese.

机构信息

Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China.

Hunan Provincial Key Laboratory of Clinical Epidemiology, Changsha 410078, China.

出版信息

Nutrients. 2021 Dec 3;13(12):4356. doi: 10.3390/nu13124356.

Abstract

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: 0.690-0.814). 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.

摘要

为了探讨体质指数(BMI)和上臂中部周长(MUAC)轨迹与糖尿病之间的关系,并评估这些模型在预测中国糖尿病前期人群中糖尿病的有效性,我们进行了这项研究。本研究采用全国性纵向研究,纳入了 1529 例病例,分析了糖尿病与 BMI 轨迹或 MUAC 轨迹之间的关系。在糖尿病前期中国人群中进行了增长混合模型分析,以探讨 BMI 和 MUAC 的轨迹,并应用逻辑回归评估这些轨迹与糖尿病风险之间的关系。接受者操作特征曲线(ROC)和曲线下面积(AUC)用于评估预测的可行性。将 BMI 和 MUAC 分别分为 4 类轨迹。BMI 和 MUAC 特定轨迹与糖尿病之间存在统计学显著关联。BMI 和 MUAC 轨迹预测糖尿病的 AUC 为 0.752(95%CI:0.690-0.814)。使用逻辑回归进行简单的交叉验证表明,预测的效率可接受。糖尿病预防计划应强调控制体重和维持骨骼肌质量的重要性,并建议糖尿病前期患者进行阻力训练。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc3e/8706558/ad367b1a5ab0/nutrients-13-04356-g001.jpg

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