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目的分析上海市浦东新区社区居民身体测量指标与血压测量值之间的关系,找到与高血压最相关的指标,为高血压高危人群的筛选提供最优预测指标、方法和依据。方法2008年4~7月期间,采用三阶段抽样方法,从上海市浦东新区随机抽取15岁及以上社区居民5 927人进行问卷调查,同时进行身高、体重、腰围、臀围及血压的测量。使用SAS 9.1和Stata 10.0软件进行数据分析。受试者操作特征(receiver operatingcharacteristics,ROC)分析用于评估每个身体测量指标作为高血压预测因子的准确性。结果调查对象中高血压患病率达30.25%,男性略高于女性,高龄组显著高于低龄组(P=0.000 1)。随着体质指数(body mass index,BMI)、腰围(waist circumference,WC)、腰臀比(waist-to-hip ratio,WHR)或腰围身高比(waist-to-height ratio,WHtR)的增加,各年龄组高血压患病率均呈显著上升趋势(P=0.001)。除了20岁以下的男性,高血压患者的BMI、WC、WHR和WHtR显著高于血压正常者(P<0.05)。这些测量指标与血压测量值呈显著的正相关(P<0.000 1)。不同性别和年龄组人群中,高血压与这些指标的关联强度不同,每个十分位变化的OR值介于1.13~1.46,低龄组关联更强,存在显著的交互作用(P<0.05)。BMI、WC、WHR和WHtR预测高血压的效果总体上不太理想:WHtR较好,男性受试者操作特征曲线下面积(area under the ROCcurve,AUC)达0.701 1,女性为0.723 9;WHR最差,男性AUC为0.652 0,女性AUC为0.670 1。各指标在不同性别和年龄组的预测效果有较大差异,但WHtR的预测效果优于WC和WHR。结论年龄、性别、BMI、WC、WHR和WHtR都与高血压有显著关联,但使用身体测量指标预测高血压的价值有限。在社区进行高血压高危人群的筛选时可考虑根据性别和年龄选择相应的身体测量指标。
Objective To analyze the relationship between body mass index and blood pressure measurement in Shanghai Pudong New Area and to find out the most relevant index of hypertension, to provide the optimal index, method and basis for the screening of high risk population of hypertension. Methods From April to July 2008, a total of 5 927 residents aged 15 years and above from 5 districts in Shanghai Pudong New Area were randomly selected for questionnaire survey by three-stage sampling method. Height, weight, waist circumference, hip circumference and blood pressure were measured simultaneously. SAS 9.1 and Stata 10.0 software for data analysis. Receiver operating characteristics (ROC) analysis was used to assess the accuracy of each body measure as a predictor of hypertension. Results The prevalence rate of hypertension in the surveyed subjects was 30.25%, slightly higher in males than in females and significantly higher in older age group than in younger age group (P = 0.000 1). With the increase of body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR) or waist-to-height ratio (WHtR) The prevalence of hypertension in all age groups showed a significant upward trend (P = 0.001). In addition to men under the age of 20, BMI, WC, WHR and WHtR were significantly higher in hypertensive patients than in those with normal blood pressure (P <0.05). These measures were significantly positively correlated with blood pressure measurements (P <0.000 1). The correlation between hypertension and these indexes was different in different gender and age groups. The odds ratio (OR) of each decile change was between 1.13 and 1.46. There was a significant correlation between hypertension and age (P <0.05). The overall effect of BMI, WC, WHR and WHtR on predicting hypertension was not so good: WHtR was better, area under the ROCcurve (AUC) of male subjects was 0.701 1, and female was 0.723 9; Poor, male AUC was 0.652 0, female AUC was 0.670 1. However, the prediction of WHtR is better than that of WC and WHR in different gender and age groups. Conclusions Age, sex, BMI, WC, WHR and WHtR are both significantly associated with hypertension, but the value of using body measures to predict hypertension is limited. In the community for the screening of high-risk groups of hypertension may be considered according to gender and age to choose the appropriate body measurements.