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目的:调查重庆市54 634例体检人群代谢综合征的患病率,评价腰围身高比对代谢综合征诊断的预测价值。方法:以中华医学会糖尿病学分会建议的标准诊断代谢综合征,描述体检人群代谢综合征的检出情况,并对人体测量学指标进行受试者工作特征曲线评价。结果:54 634例研究对象中,代谢综合征患者6 730例(患病率12.32%),男性患病率高于女性(P=0.000),代谢综合征患病率随着年龄增长而增高(P=0.000)。采用ROC曲线观察WHt R对MS的预测价值,全体受检者的AUC为0.857(95%CI=0.853~0.861),男性组和女性组的AUC分别为0.827(95%CI=0.821~0.832)和0.892(95%CI=0.886~0.899),≤44岁组、45~64岁组和≥65岁组的AUC分别为0.886(95%CI=0.880~0.892),0.812(95%CI=0.805~0.820)和0.798(95%CI=0.785~0.810)。各组的WHt R最佳切点在0.51左右(敏感度和特异度分别为:全体受检者:85.1%和72.4%,男性:82.5%和68.9%,女性:85.0%和79.3%,≤44岁组:87.8%和76.6%,45~64岁组:77.6%和71.6%,≥65岁组:77.5%和69.3%)。结论:腰围身高比对代谢综合征诊断的预测价值较高,最佳切点为0.51。
Objective: To investigate the prevalence of metabolic syndrome in 54 634 physical examination population in Chongqing and to evaluate the predictive value of waist-height-to-height ratio in the diagnosis of metabolic syndrome. Methods: According to the criteria proposed by Chinese Medical Association Diabetes Branch, the metabolic syndrome was diagnosed. The detection of metabolic syndrome was described. The anthropometric indexes were also used to evaluate the working characteristics of subjects. Results: Of the 6 634 subjects, 6 730 were patients with metabolic syndrome (prevalence 12.32%), the prevalence was higher in males than in females (P = 0.000), and the prevalence of metabolic syndrome increased with age ( P = 0.000). The AUC of WHt R was 0.857 (95% CI = 0.853-0.861). The AUC of male and female subjects were 0.827 (95% CI = 0.821-0.832) and AUC of 0.892 (95% CI = 0.886-0.899), ≤44 years old, 45-64 years old and ≥65 years old were 0.886 (95% CI 0.880-0.892), 0.812 (95% CI 0.805-0.820 ) And 0.798 (95% CI = 0.785-0.810). The WHt R best cut-point in each group was about 0.51 (sensitivity and specificity were 85.1% and 72.4% for all subjects, 82.5% and 68.9% for men, 85.0% and 79.3% for women, and ≤44 87.8% and 76.6% in the old group, 77.6% and 71.6% in the 45-64 year group, and 77.5% and 69.3% in the group of 65 or older). Conclusion: The height to waist ratio is more predictive for the diagnosis of metabolic syndrome, the best cut point is 0.51.