目的 探讨在人群水平上不同暴露对心血管疾病的"贡献",构建风险预测模型,对于有效分配预防资源有重要意义.方法 采用CHNS(China Health and Nutrition Survey,中国健康与营养调查)数据库2009、2011及2015年中东部地区10个省市(北京、辽宁、黑龙江、上海、山东、河南、湖北、湖南、广西及江苏)35～75岁9 899例常住居民作为研究对象.单因素分析纳入变量(性别、年龄、BMI、婚姻状况、城乡、睡眠时间、吸烟、饮酒、糖尿病、教育程度及医保),在logistic回归分析危险因素基础上,估计某(些)危险因素的多因素调整人群归因危险度,随机抽取70％(n=6 927)为建模组,30％(n=2 974)为验证组,构建CVD风险预测模型,同时利用受试者特征工作曲线(Receiver operating characteristic curve,ROC)及 Hosmer-Lemeshow 拟合优度检验(Good of fit test)评估风险预测模型区分度和校准度.结果 BMI、睡眠时间、吸烟、饮酒以及糖尿病的调整人群归因危险度与95％置信区间分别为32.20％(27.67％～36.89％)、7.90％(1.68％～16.58％)、18.56％(11.35％～26.24％)、6.47％(0.11％～13.25％)、5.73％(4.42％～7.03％).多因素调整人群归因危险度百分比结果表明,BMI在心血管疾病患病病因中占主导地位,吸烟影响次之,睡眠时间、饮酒及糖尿病影响较弱.低风险患病率为18.44％,较高风险的患病率为14.19％,高风险患病率为42.52％.ROC曲线下面积AUC=0.711,P＜0.001;Hosmer-Lemeshow拟合优度P=0.257.结论 未来应重点关注高风险人群,控制体质指数到正常范围,减少吸烟,对预防心血管疾病有重大意义.风险预测模型具有较好的区分性和实用性等价值,可为预防心血管疾病提供一定的预测能力.
Population-attributable risk assessment and risk prediction model of cardiovascular disease risk factors
Objective To explore the"contribution"of different exposures to cardiovascular diseases at the population level and to construct a risk prediction model for the effective allocation of prevention resources.Methods The CHNS(China Health and Nutrition Survey)database was used.In 2009,2011 and 2015,9 899 permanent residents aged 35 to 75 years in 10 provinces and cities in the central and eastern regions(Beijing,Liaoning,Heilongjiang,Shanghai,Shandong,Henan,Hubei,Hunan,Guangxi and Jiangsu)were selected as the research subjects.A single-factor analysis was conducted to examine the risk factors including sex,age,BMI,marital status,urban/rural area,sleep time,smoking,alcohol consumption,diabetes,education,and health insurance.The multifactor-adjusted population-attributable risk of certain risk factors was also estimated based on logistic regression analysis.The cardiovascular disease(CVD)risk prediction model was developed using a modeling group of 6 927 randomly selected individuals(70％)and a validation group of 2 974 individuals(30％).The model's differentiation and calibration were assessed using the receiver operating characteristic(ROC)curve and the Hosmer-Lemeshow goodness-of-fit test.Results The results showed that the adjusted population attributable risk and 95％confidence interval for BMI,sleep time,smoking,drinking and diabetes were 32.20％(27.67％-36.89％),7.90％(1.68％-16.58％),18.56％(11.35％-26.24％),6.47％(0.11％-13.25％)and 5.73％(4.42％-7.03％).The results of multivariate adjusted population attributable risk percentage showed that BMI was the dominant cause of cardiovascular diseases,followed by smoking,sleep time,drinking and diabetes.The low-risk prevalence rate was 18.44％,the higher-risk prevalence rate was 14.19％,and the high-risk prevalence rate was 42.52％.The area under ROC curve AUC was 0.711,P＜0.001,and Hosmer-Lemeshow goodness of fit test showed P=0.257.Conclusion In the future,it is important to focus on high-risk groups,control body mass index to the normal range,and reduce smoking,which is of great significance for the prevention of cardiovascular diseases.The risk prediction model has the value of good differentiation and practicability,and can provide certain prediction ability for the prevention of cardiovascular diseases.
Cardiovascular diseasePopulation attributable risk percentageRisk prediction modelCentral and eastern regions
万方数据
维普
