College of Public Health, Xinjiang Medical University, Ürümqi, 830011, China.
Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Ürümqi, 830011, China.
Sci Rep. 2020 Jul 14;10(1):11600. doi: 10.1038/s41598-020-68383-7.
Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and gallbladder disease. The area under ROC was 0.811 for development group and 0.814 for validation group, and the p values of the two calibration curves were 0.053 and 0.438, the improvement of net reclassification and integrated discrimination are significant in our model. Our results give a clue that the screening models we conducted may be useful for identifying Chinses adults at high risk for diabetes. Further studies are needed to evaluate the utility and feasibility of this model in various settings.
我们的研究旨在建立和验证一种简单的 2 型糖尿病（T2DM）筛查模型，以识别中国成年人中的高危个体。共有 643439 名参加国家健康检查的受试者被纳入这项横断面研究。在排除有缺失数据或既往病史的受试者后，最终有 345718 名成年人纳入了最终分析。我们使用最小绝对收缩和选择算子模型进行特征选择优化，并使用多变量逻辑回归分析建立预测模型。结果表明，T2DM 的主要危险因素是年龄、性别、不饮酒或饮酒时间>25g、不运动、吸烟、腰高比、心率、收缩压、脂肪肝和胆囊疾病。在开发组和验证组中，ROC 曲线下面积分别为 0.811 和 0.814，两个校准曲线的 p 值分别为 0.053 和 0.438，模型的净重新分类和综合判别改善均有显著意义。我们的研究结果表明，我们建立的筛查模型可能有助于识别中国成年人患糖尿病的高危人群。需要进一步的研究来评估该模型在各种环境下的实用性和可行性。
