目的: 代谢综合征（metabolic syndrome,MetS）发病率逐年升高,正威胁着全球人类健康,本研究旨在构建简易高效的代谢综合征识别模型。方法: 本研究采用中国健康与养老追踪调查数据库中45岁以上的中老年人群的人体测量学资料（2011年）,最终纳入7552例受试者,按照7∶3的比例随机分割为模型训练集与模型验证集,采用多因素逐步Logistic回归分析构建MetS识别模型并构建列线图,通过ROC曲线下面积评估列线图的筛查性能,应用决策曲线分析计算模型的净效益。结果: 我国45岁以上中老年人群MetS的患病率经年龄标化后为42.22%。模型显示,女性、高血脂、糖尿病、吸烟、高收缩压、快脉搏、宽腰围、高BMI为MetS的危险因素。本模型C指数为0.864。列线图最佳阈值概率为0.407。训练集ROC曲线的AUC为0.864（0.854~0.874）,验证集ROC曲线的AUC为0.857（0.842~0.873）。当将阈值概率设置为0.407时,该模型的灵敏度为80%（95%CI：78.35%~81.67%）,特异度为78%（95%CI：76.57%~79.51%）。决策曲线分析显示,采用本模型进行MetS筛查时可使33人/每百人免除不必要的MetS确诊试验。结论: 目前我国中老年人群中代谢综合征患病率较高,本研究构建的识别模型有助于中国45岁以上人群MetS患者的早期筛查。
Abstract
Objective The incidence of Metabolic syndrome (MetS) is increasing year by year, which is threatening human health worldwide. The aim of this study is to construct a simple and efficient metabolic syndrome identification model. Methods This study used anthropometric data from the China Health and Retirement Longitudinal Survey (2011). A total of 7552 subjects aged 45 years and over were included and randomly divided into training set and validation set according to the ratio of 7∶3. Multivariate stepwise logistic regression analysis was used to construct a MetS identification model and a nomogram. The screening performance of the nomogram was evaluated by the area under the ROC curve, and the net benefit of the model was calculated by decision curve analysis. Results The age-standardized prevalence of MetS was 42.22% among Chinese middle-aged and elderly people over 45 years old. The model showed that female, hyperlipidemia, diabetes, smoking, high systolic blood pressure, fast pulse, wide waist circumference, and high BMI were risk factors for MetS. The C-index of the model was 0.864. The optimal threshold probability of the nomogram was 0.407. The AUC of ROC curve in training set was 0.864(0.854-0.874), and the AUC of ROC curve in validation set was 0.857(0.842-0.873). When the threshold probability was set to 0.407, the sensitivity of the model was 80% (95%CI: 78.35%-81.67%), and the specificity was 78% (95%CI: 76.57%-79.51%). Decision curve analysis showed that 33 persons per 100 persons could be exempted from unnecessary MetS confirmatory tests when MetS screening was performed by using this model. Conclusion The prevalence of MetS is high in middle-aged and elderly people in China. The identification model constructed in this study is helpful for the early screening of mets in Chinese people over 45 years old.
关键词
代谢综合征 /
危险因素 /
识别模型 /
列线图 /
决策曲线
Key words
the metabolic syndrome /
risk factors /
model of identification /
nomogram /
decision curve
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基金
安徽省重点研究与开发计划“代谢综合征患者的识别与2年列队研究”（202004j07020026）
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