Characteristics of methadone maintenance treatment clinic patients and influencing factors for HBsAg positivity based on Bayesian network model
10.3760/cma.j.issn.0254-6450.2020.03.010
- VernacularTitle: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
- Author:
Zhihong SHAO
1
;
Jing SHI
;
Tian YAO
;
Dan FENG
;
Shuang DONG
;
Shan SHI
;
Yongliang FENG
;
Yawei ZHANG
;
Suping WANG
Author Information
1. 山西医科大学公共卫生学院流行病学教研室，太原 030001
- Keywords:
Methadone maintenance treatment;
HBsAg;
Characteristics;
Bayesian network model;
Influencing factors
- From:
Chinese Journal of Epidemiology
2020;41(3):331-336
- CountryChina
- Language:Chinese
-
Abstract:
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.
