文章摘要
邵志宏,石璟,姚添,冯丹,董爽,石珊,冯永亮,Zhang Yawei,王素萍.美沙酮维持治疗门诊患者特征和HBsAg阳性影响因素的贝叶斯网络模型分析[J].中华流行病学杂志,2020,41(3):331-336
美沙酮维持治疗门诊患者特征和HBsAg阳性影响因素的贝叶斯网络模型分析
Characteristics of methadone maintenance treatment clinic patients and influencing factors for HBsAg positivity based on Bayesian network model
收稿日期:2019-07-09  出版日期:2020-04-01
DOI:10.3760/cma.j.issn.0254-6450.2020.03.010
中文关键词: 美沙酮维持治疗  乙型肝炎表面抗原  特征  贝叶斯网络模型  影响因素
英文关键词: Methadone maintenance treatment  HBsAg  Characteristics  Bayesian network model  Influencing factors
基金项目:国家科技重大专项(2018ZX10721202,2012ZX10002001)
作者单位E-mail
邵志宏 山西医科大学公共卫生学院流行病学教研室, 太原 030001  
石璟 山西医科大学公共卫生学院流行病学教研室, 太原 030001  
姚添 山西医科大学公共卫生学院流行病学教研室, 太原 030001  
冯丹 山西医科大学公共卫生学院流行病学教研室, 太原 030001  
董爽 山西医科大学公共卫生学院流行病学教研室, 太原 030001  
石珊 南宁市红十字会医院美沙酮门诊 530012  
冯永亮 山西医科大学公共卫生学院流行病学教研室, 太原 030001  
Zhang Yawei 耶鲁大学公共卫生学院环境健康科学系, 美国康涅狄格州纽黑文市 06520  
王素萍 山西医科大学公共卫生学院流行病学教研室, 太原 030001 spwang88@163.com 
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中文摘要:
      目的 了解美沙酮维持治疗(MMT)门诊患者的特征,探讨HBsAg阳性的影响因素及因素间复杂的网络关系。方法 于2014年9-11月对广西壮族自治区3个MMT门诊正在接受治疗的1 040名患者,采用面对面问卷调查、病历查阅等方式收集其一般人口学特征、吸毒情况、MMT情况、性行为、抗-HCV、HIV感染情况等,检测HBsAg、抗-HBs、抗-HCV情况,通过χ2检验、非条件logistic回归和贝叶斯网络模型分析HBsAg阳性的影响因素及因素间复杂的网络关系。结果 研究对象1 031例,HBsAg阳性率为11.35%(117/1 031),抗-HCV阳性者740例,HBsAg阳性率为10.27%(76/740)。控制混杂因素后,抗-HBs阳性与阴性者相比,不易出现HBsAg阳性(OR=0.05,95%CI:0.03~0.09);抗-HCV阳性与阴性者相比,也不易出现HBsAg阳性(OR=0.30,95%CI:0.17~0.52);有乙型肝炎(乙肝)家族史比没有乙肝家族史者更容易出现HBsAg阳性(OR=5.30,95%CI:2.68~10.52)。贝叶斯网络模型结果显示:乙肝家族史、抗-HBs与HBsAg阳性直接相关,抗-HCV、最近3个月注射吸毒、治疗期间吸食其他毒品与HBsAg阳性间接相关。结论 MMT门诊患者中抗-HBs、乙肝家族史、抗-HCV、最近3个月注射吸毒及治疗期间吸食其他毒品与HBsAg阳性相关。
英文摘要:
      Objective To understand the characteristics and explore the influencing factors of HBsAg positivity in methadone maintenance treatment (MMT) clinic patients. Methods A face to face interview and medical record review were conducted in 1 040 patients at three MMT clinics in Guangxi from September to November in 2014. The questionnaire information included general demographic characteristics, drug use history, MMT status, sexual behaviors, and health status, etc. Blood samples were collected from the patients at the same time for the detections of the level of HBsAg,anti-HBs and anti-HCV. By using χ2 test, unconditional logistic regression model and Bayesian network model the influencing factors for HBsAg positivity in MMT clinic patients and the complex network relationship among these factors were explored. Results A total of 1 031 MMT clinic patients were surveyed, the HBsAg positive rate was 11.35% (117/1 031). The anti-HCV positive rate was 71.77% (740/1 031), among the anti-HCV positive patients, the HBsAg positive rate was 10.27% (76/740). After adjusting for the confounding factors, anti-HBs positive persons might not be HBsAg positive (OR=0.05, 95%CI:0.03-0.09), and anti-HCV positive persons might not be HBsAg positive too (OR=0.30, 95%CI:0.17-0.52) compared with anti-HBs negative and anti-HCV negative persons, respectively. The persons with family history of hepatitis B virus infection were more likely to be HBsAg positive compared those with no such family history (OR=5.30, 95%CI:2.68-10.52). Bayesian network model analysis results showed that family history of hepatitis B virus infection and anti-HBs were directly related with HBsAg positivity. Anti-HCV, intravenous drug use in the past three months and other drug using during treatment were indirectly related with HBsAg positivity. Conclusions Anti-HBs, family history of hepatitis B virus infection, anti-HCV, intravenous drug use in past three months and other drug use during treatment were related with the HBsAg positivity in MMT clinic patients. So, it is necessary to enhance health education, improve health awareness and decrease high risk behaviors to reduce the rate of HBV infection.
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