Predictors of Hepatitis C Virus Infections Among People Who Injects Drug in Negeri Sembilan

Azline Abdilah, Sri Ganesh Muthiah: Predictors of Hepatitis C Virus Infections Among People Who Injects Drug in Negeri Sembilan. 2019, (Type: POSTER PRESENTATION; Organisation:).

Abstract

INTRODUCTION: Hepatitis C virus (HCV) infection is known among the major cause of morbidity and mortality globally. Persistent HCV infection is associated with major liver complications such as liver failure, liver cancer, and fatality. Estimated that 5.6 million people who inject drugs (PWID) were chronically infected with HCV globally. In Malaysia estimated that 59% of HCV infections were among PWID. The study is aimed to determine the prevalence of HCV infection and its predictors among PWID in Negeri Sembilan. METHODS: A cross-sectional study based on random proportion to size sampling was conducted among 212 out of 1414 registered Methadone Maintenance Therapy (MMT) clients with PWID attending health clinics in Negeri Sembilan from February 2018 to July 2018. Data were collected using a face-to-face interview with an administered questionnaire. Data were analysed using the Statistical Package of IBM SPSS Statistics Version 23 and p-value of <0.05 is considered significant. Independent T-test and Chi-square test (c2) was used to determine the associations between the variables, and multiple logistic regressions were used for predictors of HCV infection among PWID. Result: A total of 212 respondents were consented and managed to complete the questionnaires given. The prevalence of HCV infections among the respondents was 89%. The predictors of HCV were age (aOR 1.07, 95%CI: 1.032, 1.110) and higher frequency of injections (aOR 5.98, 95%CI: 3.110, 11.476). Conclusion: HCV prevalence is higher among PWID in Negeri Sembilan. Effective and efficient prevention and control activities should focus on the identified predictors.

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    @proceedings{APCPH-2019-233,
    title = {Predictors of Hepatitis C Virus Infections Among People Who Injects Drug in Negeri Sembilan},
    author = {Azline Abdilah and Sri Ganesh Muthiah},
    year  = {2019},
    date = {2019-07-22},
    urldate = {2019-07-22},
    journal = {6th Asia-Pacific Conference on Public Health 2019 Proceedings},
    issue = {6},
    abstract = {INTRODUCTION: Hepatitis C virus (HCV) infection is known among the major cause of morbidity and mortality globally. Persistent HCV infection is associated with major liver complications such as liver failure, liver cancer, and fatality. Estimated that 5.6 million people who inject drugs (PWID) were chronically infected with HCV globally. In Malaysia estimated that 59% of HCV infections were among PWID. The study is aimed to determine the prevalence of HCV infection and its predictors among PWID in Negeri Sembilan. METHODS: A cross-sectional study based on random proportion to size sampling was conducted among 212 out of 1414 registered Methadone Maintenance Therapy (MMT) clients with PWID attending health clinics in Negeri Sembilan from February 2018 to July 2018. Data were collected using a face-to-face interview with an administered questionnaire. Data were analysed using the Statistical Package of IBM SPSS Statistics Version 23 and p-value of \<0.05 is considered significant. Independent T-test and Chi-square test (c2) was used to determine the associations between the variables, and multiple logistic regressions were used for predictors of HCV infection among PWID. Result: A total of 212 respondents were consented and managed to complete the questionnaires given. The prevalence of HCV infections among the respondents was 89%. The predictors of HCV were age (aOR 1.07, 95%CI: 1.032, 1.110) and higher frequency of injections (aOR 5.98, 95%CI: 3.110, 11.476). Conclusion: HCV prevalence is higher among PWID in Negeri Sembilan. Effective and efficient prevention and control activities should focus on the identified predictors.},
    note = {Type: POSTER PRESENTATION; Organisation:},
    keywords = {Hepatitis C Virus, predictors, prevalence, PWID},
    pubstate = {published},
    tppubtype = {proceedings}
    }