文章摘要
胡培,钟斐,程伟彬,徐慧芳,凌莉.广州市男男性行为者艾滋病感染风险模型的建立[J].中华流行病学杂志,2012,33(7):667-671
广州市男男性行为者艾滋病感染风险模型的建立
Study on the infectious risk model of AIDS among men who have sex with men in Guangzhou
收稿日期:2012-02-09  出版日期:2014-09-09
DOI:
中文关键词: 男男性行为者  艾滋病感染风险评估模型
英文关键词: Men who have sex with men  Acquired immune-deficiency syndrome health risk appraisal
基金项目:广东省医学科研基金(B2010277);广州市医药卫生科技项目(201102A211001);中盖艾滋病项目
作者单位E-mail
胡培 中山大学公共卫生学院医学统计与流行病学系, 广州 510080  
钟斐 中山大学公共卫生学院医学统计与流行病学系, 广州 510080
广州市疾病预防控制中心艾滋病预防控制科 
 
程伟彬 广州市疾病预防控制中心艾滋病预防控制科  
徐慧芳 广州市疾病预防控制中心艾滋病预防控制科  
凌莉 中山大学公共卫生学院医学统计与流行病学系, 广州 510080 lingli@mail.sysu.edu.cn 
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中文摘要:
      目的 建立一种适合广州市男男性行为者(MSM)的艾滋病感染风险评估模型,为后续的健康教育和行为干预提供丁具.方法 利用广州市疾病预防控制中心2008-2010年MSM艾滋病病毒(HIV)横断面监测资料,采用logistic回归筛选MSM感染HIV的危险因素,运用统计模型计算个体和群体危险分值,评估个体艾滋病感染风险.结果 logistic回归纳入MSM感染的HIV危险因素为年龄、户籍所在地、月经济收入、寻找性伴的主要场所、最近1年HIV检测、第一次性行为年龄、最近6个月安全套使用、性病相关症状、梅毒;建立危险分值及人群危险分值表.人群平均危险分值为6.06,HIV阴性/阳性者感染风险评分均数为3.10/18.08(P<0.001).不同危险评分组别(≤-20、-20 ~0、0~20、20~ 40、>40)的HIV感染率为0.9%、2.0%、7.0%、14.4%、33.3%.评分预测的灵敏度为54.4%,特异度为75.4%,总准确率为74.2%.结论 HIV感染风险模型能有效评估MSM艾滋病感染HIV风险,帮助个体识别高危行为,是个体化的HIV健康教育与行为干预的工具.
英文摘要:
      Objective To develop a human immune-deficiency virus (HIV) infection risk appraisal model suitable for men who has sex with men (MSM) in Guangzhou,and to provide tools for follow-up the outcomes on health education and behavior intervention.Methods A cros-sectional study was conducted in Guangzhou from 2008 to 2010.Based on the HIV surveillance data,the main risk factors of HIV infection among MSM were screened by means of logistic regression.Degree on relative risk was transformed into risk scores by adopting the statistics models.Individual risk scores,group risk scores and individual infection risk in comparison with usual MSM groups could then be calculated according to the rate of exposure on those risk factors appeared in data from the surveillance programs.Results Risk factors related to HIV infection among MSM and the quantitative assessment standard (risk scores and risk scores table of population groups) for those factors were set up by multiple logistic regression,including age,location of registered residence,monthly income,major location for finding their sexual partners,HIV testing in the past year,age when having the first sexual intercourse,rate of condom use in the past six months,symptoms related to sexually transmitted diseases (STDs) and syphilis in particular.The average risk score of population was 6.06,with risk scores for HIV positive and negative as 3.10 and 18.08 respectively (P< 0.001 ).The rates of H IV infection for different score groups were 0.9%,2.0%,7.0%,14.4% and 33.3%,respectively.The sensitivity and specificity on the prediction of scores were 54.4% and 75.4% respectively,with the accuracy rate as 74.2%.Conclusion HIV infection risk model could be used to quantify and classify the individual' s infectious status and related factors among MSM more directly and effectively,so as to help the individuals to identify their high-risk behaviors as well as lifestyles.We felt that it could also serve as an important tool used for personalized HIV health education and behavior intervention programs.
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