目的 应用受试者工作特征曲线法(ROC曲线法)探索北京市居民传染病健康素养判定标准的最佳界值点.方法 分析数据来源于北京市居民传染病健康素养调查.以自报健康水平(健康状况是否为不好或很不好)为“金标准”,应用ROC法确定判定标准的最佳界值点.应用非条件Logistic回归法分析是否具备传染病健康素养与自报健康水平之间的相关性.结果 ROC曲线分析结果显示,最佳临界点为得分等于1.55分(总分3分),ROC曲线下面积为0.664(95％CI:0.641-0.688),灵敏度、特异度分别为0.672和0.569.依据最佳临界点将居民划分为是否具备传染病健康素养(传染病健康素养得分达到1.55分).北京市居民具备传染病健康素养的比例为65.9％.非条件Logistic回归分析结果显示,不具备传染病健康素养者自报健康较差(不好或很不好)的比例高于具备者(OR=1.958,95％ CI:1.646-2.329).结论 ROC曲线法是构建健康素养判定标准的科学方法.本研究确定的判定标准能够明显筛查出不良健康后果,具有一定的筛查价值.%Objective To explore the cut-off value for infectious diseases health literacy (HL) among residents in Beijing by using receiver operating characteristic (ROC) curve. Methods The data was from Survey on Infectious Dis-eases HL in Beijing. The best cut-off value was detected by using ROC curve with self-reported health status ( bad or worse) as golden criterion. Logistic regression model was used to analyze the relationship between the level of HL and self-reported health status. Results The results of ROC curves demonstrated the best cut-off value was 1.55 points (total points; 3) , and the area under ROC curve was 0. 664 (95% CI; 0.641-0.688). Sensitivity and specificity was 0. 672 and 0.569, respectively. Residents were categorized into satisfied infectious diseases HL group (scored above 1.55 points) and unsatisfied group ( scored less than 1. 55 points) . According to the best cutoff value (1. 55 points) , 65. 9% of participants had satisfied infectious diseases HL in Beijing. Logistic regression model revealed that the percentage of par-ticipants who self-reported bad or worse health status in unsatisfied HL group was higher than that in satisfied HL group ( OR = 1. 958 , 95% CI:1. 646 - 2. 329). Conclusion ROC curve was an appropriate tool to explore the reference values for health literacy. The cut-off value of infectious disease HL found in this study provided a reference for sorting satisfied HL residents and screening their health status.
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