基于代谢综合征因子新疆农村居民冠状动脉粥样硬化性心脏病发病风险预测模型构建

Establishment of a metabolic syndrome factors-based coronary heart disease risk prediction model for rural residents in Xinjiang Uygur Autonomous Region

目的基于代谢综合征(MS)因子构建新疆农村居民冠状动脉粥样硬化性心脏病(CHD)发病风险预测模型,为该人群CHD的防治工作提供参考依据。方法采用多阶段分层整群随机抽样方法分别于2010年4月、2012年12月和2016年11月在新疆伊犁新源县、喀什伽师县和第三师51团抽取16853名农村居民进行基线调查,于2013-2017年对新源县和喀什伽师县、2019-2021年对第三师51团进行3次随访调查,以随访满5年的13647名农村居民作为研究对象,随机抽取其中2/3作为训练样本(9155人),剩余1/3作为验证样本(4492人);对训练样本中3206例MS人群进行因子分析,研究MS潜在聚集模式并提取与CHD相关的潜在因子,采用多因素Cox比例风险回归分析方法构建CHD发病风险预测模型,并绘制受试者工作特征曲线(ROC)评价模型的预测效能。结果新疆农村居民的CHD累计发病率为4.94%,训练样本和验证样本的CHD累计发病率均为4.94%;因子分析结果显示,训练样本MS患者中共提取出肥胖因子、血压因子、血脂血糖因子、肾代谢因子、蛋白因子、肝酶因子、心肌酶因子和胆红素因子8个潜在因子构建CHD预测模型,累计方差贡献率为77.905%;多因素Cox比例风险回归分析结果显示,女性、年龄较高、肥胖因子、胆红素因子、血压因子和血脂血糖因子均为训练样本和验证样本CHD发病的危险因素;ROC曲线分析结果显示,训练样本ROC曲线下面积(AUC)为0.762(95%CI=0.742~0.782),验证样本AUC为0.774(95%CI=0.742~0.805)。结论基于MS因子构建的新疆农村居民CHD预测模型适用于当地居民CHD发病的风险预测,可用于该人群CHD的指导预防工作。

Objective To construct a metabolic syndrome(MS)factors-based model for predicting the risk of coronary heart disease(CHD)among rural residents of Xinjiang Uygur Autonomous Region(Xinjiang)for CHD prevention and treatment in the population.Methods Complete baseline information were collected through face-to-face questionnaire interview,physical examination and laboratory tests from 16853 of 18524 adult rural residents(aged≥18 years)recruited with multistage stratified cluster random sampling at two counties of Xinjiang and a division of Xinjiang Production and Construction Corps during April 2010,December 2012 and November 2016.Subsequent follow-up surveys were carried out among the eligible participants from April 2013 to July 2021 and finally 3647participants with a follow-up period of five years and more(averagely 5.28±1.67 years)and without CHD at the baseline survey were included in the analysis,of which,two-thirds(n=9155)were randomly assigned into a training set and onethird(n=4492)into a verification set.Factor analysis was performed base on the data of 3206 MS sufferers identified in the participants of training set to explore potential clustering pattern of MS components and probable CHD-related factors.Multivariate Cox proportional risk regression analysis was used to construct prediction model for CHD risk and receiver operating characteristic curve(ROC)analysis was adopted to evaluate the efficiency of the prediction model constructed.Results The cumulative incidence of CHD was 4.94%for all the participants and for those of training and verification set.Training set data-based factor analysis revealed potential CHD-related factors for prediction model construction:obesity,blood pressure,blood lipid/glucose,renal metabolism,blood protein,liver enzyme,myocardial enzyme,and bilirubin and the 8 factors could explain 77.905%of the cumulative variance.Cox proportional hazard regression analysis showed that being female,at older age,obesity,low bilirubin,high blood pressure,and high blood lipid and glucose were risk factors of CHD for the participants of training and verification set.The area under the ROC curve(AUC)was 70.62(95%confidence interval[95%CI]:0.742-0.782)for the prediction derived from training set data and 0.774(95%CI:0.742-0.805)for the prediction derived from validation set data.Conclusion A MS factor-based prediction model for predicting CHD risk among rural residents in Xinjiang was constructed and the model could be used in CHD risk assessment and management in local population.