Next Article in Journal
An Umbrella Review and Narrative Synthesis of the Effectiveness of Interventions Aimed at Decreasing Food Prices to Increase Food Quality
Previous Article in Journal
Reliability of the 30 s Chair Stand Test in Women with Fibromyalgia
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
IJERPH
Volume 16
Issue 13
10.3390/ijerph16132345
ijerph-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Factors Correlating to the Development of Hepatitis C Virus Infection among Drug Users—Findings from a Systematic Review and Meta-Analysis

by
Biao Zhou
1,†,
Gao Feng Feng Cai
1,†,
Hua Kun Kun Lv
1,2,†,
Shuang Fei Fei Xu
1,
Zheng Ting Ting Wang
1,
Zheng Gang Gang Jiang
1,
Chong Gao Gao Hu
1,* and
Yong Di Di Chen
1,*
1
Department of Scientific Research and Information Management, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Binsheng Road, Hangzhou 310051, China
2
Department of Immunization planning, Zhejiang provincial key laboratory of infectious disease vaccine and prevention and control. 3399 Binsheng Road, Hangzhou 310051, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to the work.
Int. J. Environ. Res. Public Health 2019, 16(13), 2345; https://doi.org/10.3390/ijerph16132345
Submission received: 23 June 2019 / Accepted: 30 June 2019 / Published: 2 July 2019
Browse Figures
Review Reports Versions Notes

Abstract

:
Hepatitis C remains a significant public health threat. However, the main routes of transmission have changed since the early 1990s. Currently, drug use is the main source of hepatitis C virus (HCV) infection, and some measures have been successively implemented and additional studies have been published. However, the factors correlating with HCV infection failed to clearly define. Our study pooled the odds ratios (ORs) with 95% confidence intervals (CIs) and analyzed sensitivity by searching data in the PubMed, Elsevier, Springer, Wiley, and EBSCO databases. Publication bias was determined by Egger’s test. In our meta-analysis, HCV-infected and non-HCV-infected patients from 49 studies were analyzed. The pooled ORs with 95% CIs for study factors were as follows: Injecting drug use 10.11 (8.54, 11.97); sharing needles and syringes 2.24 (1.78, 2.83); duration of drug use >5 years 2.39 (1.54, 3.71); unemployment 1.50 (1.22, 1.85); commercial sexual behavior 1.00 (0.73, 1.38); married or cohabiting with a regular partner 0.88 (0.79, 0.98), and sexual behavior without a condom 1.72 (1.07, 2.78). This study found that drug users with histories of injecting drug use, sharing needles and syringes, drug use duration of >5 years, and unemployment, were at increased risk of HCV infection. Our findings indicate that sterile needles and syringes should be made available to ensure safe injection. In view of that, methadone maintenance treatment can reduce or put an end to risky drug-use behaviors, and should be scaled up further, thereby reducing HCV infection.

1. Introduction

Hepatitis C is a viral infectious disease caused by the HCV, which is characterized by diffuse liver damage [1]. In 2003, the World Health Organization (WHO) estimated that the global prevalence of HCV infection was about 3.0%, with about 3–4 million new infections every year, about 130–150 million chronic infections worldwide, and about 672,000 deaths annually from acute viral hepatitis C infections and hepatitis C-related liver cancer and cirrhosis [2]. At present, the new curative treatment for HCV infection, e.g., directly acting antiviral, was available and convinced in safety, and tolerability [3,4,5].
However, the main route of HCV infection has changed since the early 1990s. Before the 1990s, blood transfusions and the use of contaminated blood products were the main sources of HCV infection [2,3,4,5,6]. Whereas currently, drug use is the main source of HCV infection in most developed and developing countries [2], and statistics have shown that over 50% of drug users are intravenous drug users [7,8,9], with an estimated 12 million injecting drug users worldwide [10]. HCV infection rates have been increasing since 2006 in some areas, especially among the younger population [9]. In addition, in the last 10 years, the number of new drug users has been increasing and there are various ways of drug use [11,12,13,14]. Pan et al. also showed that the club drug users had a high prevalence of HCV infection, as well as people with high-frequency unprotected sexual behavior and less available intervention services [15]. These findings suggest that new drugs have become a new threat to human health.
In fact, in recent times, the number of global drug users has increased rapidly, from 185 million in 2004 to 250 million in 2015 [10,16]. Similarly, the number of registered drug users in China has risen rapidly, from 70,000 in 1990 to 3 million in 2015 [17]. In view of this significant population of drug users and the risk of cross infection with HCV among drug users, the impact of HCV infection among this population remains significant and constitutes a major health burden.
In recent years, some practical measures and strategies have been implemented to tackle the spread of infections among drug users, such as publicizing health information, making condoms available in public places, providing needle/syringe exchange centers, as well as opening methadone maintenance treatment clinics that help reduce risky drug-use behaviors thereby reducing the risk of transmission of blood-borne infections [8,18,19,20,21,22,23,24,25]. However, the rates of HCV infection remain high among drug users [25,26]. Many factors influence the development of HCV infection among drug users, such as injecting behavior, sharing needles and/or syringes, the duration of drug use, and high-risk sexual behavior [27,28,29,30,31,32,33,34,35].
In 2006, Xia et al. performed meta-analysis on data collected from drug users in China to determine factors that correlate with the occurrence of HCV infection [26], and Stone et al. performed another meta-analysis for incarceration history and risk of HCV acquisition among people who injected drugs in 2018 [36]. In another study, Hagan et al. collected data from published or released reports between January 1989 and December 2006 and data from scientific conferences between December 2006 April 2010, and meta-analyzed the effects of risk-reduction interventions [25]. They concluded that combined substance-use treatment and support for safe injection were the most effective interventions for reducing HCV seroconversion. These findings implied that appropriate intervention can prevent HCV infection among injection drug users. Studies have also demonstrated that the hazards posed by certain risk factors can be controlled. However, this meta-analysis was performed on a limited number of studies and limitations were imposed as a result of literature being unavailable. For example, in 2004, Lin et al. completed a quasi-experiment design in a controlled community intervention study that included a needle and syringe exchange program, peer education and health education, provision of free needles and syringes, and the collection of used needles, which was implemented for 10 months to injecting drug users in an intervention community, but no intervention measures were implemented in a control community for comparison [37]. A number of other studies investigating factors correlating to HCV infection in drug users have been published since 2006 [27,28,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77]; however, the contribution of each of the factors identified in such studies remains unclear or in some cases is even contradictory.

2. Materials and Methods

2.1. Literature Search Strategy

Searches were performed in specified databases on the BoKu data service platform. We used the following search terms “Hepatitis C or HCV” and “drug use or drug addiction” in the search field “Title/Abstract,” and searched six international databases, namely PubMed, OVID, Springer, Wiley, Elsevier, and EBSCO. We also used the search terms “Hepatitis C or “HCV” and “drug use or drug addiction” in the search field “Abstract,” and searched the Chinese Medical Journal Database and Chinese National Knowledge Infrastructure. The searches were completed in the last week of March 2019.

2.2. Inclusion and Exclusion Criteria

The eligibility criteria for the studies included in this meta-analysis were: (1) The study is an original research; (2) the study was an observational study with specific temporal and geographic characteristics; (3) the study was published with the full text available; (4) all cases and controls were drug users and the source of research objects was clearly stated; (5) major influencing factors were reported; and (6) hepatitis C was diagnosed by the national diagnostic criteria that existed at that time [78].
Literature was excluded from the meta-analysis when: (1) Based on the data reported, the odds ratio (OR) with 95% confidence interval (CI) could not be achieved by calculating the major influencing factors; (2) the literature duplicated the same research; (3) according to the source of the research objects, the province (state) was used as the screening repeated research object analysis unit and for studies with the same or cross research objects, only one of the studies was included and the others were excluded; and (4) according to the declaration by Ebrahim et al., the literature satisfying the number of items in the corresponding research type declaration was less than half the total number of items [79,80].

2.3. Data Extraction

A pre-made form was used for data extraction. The literature was assessed one-by-one and the form was completed by two trained reviewers. The following data were extracted from the qualified studies: First author, year of the study, location, sample size, the number of drug users in the HCV-infected group and the non-HCV-infected group, the number of males and females or the male to female ratio, and age distribution among drug users.
Discrepancies between the assessment results acquired by the two reviewers were resolved by checking the original documents and discussing.

2.4. Sensitivity Analysis

In this meta-analysis, the studies with the maximum weight were omitted from the subgroup analysis. The remaining studies were pooled, and the pooled ORweight values with 95% CIs for each study factor were obtained. The pooled ORweight values were then compared with the pooled ORs before being omitted from the study.

2.5. Statistical Analysis

In this meta-analysis, the main indicators were the ORs with 95% CIs. Following a heterogeneity test, the fixed effects model was used to analyze factors without heterogeneity for the different studies and the random effect model was used to analyze factors with heterogeneity using the Review Manager 5.1 software. (Cochrane Collaboration, Rigshospitalet, Denmark). Heterogeneity was evaluated using Cochran’s chi-square test with a significance level of α = 0.1 and using I2 statistics with heterogeneity accepted as I2 ≤ 50% [81]. In this meta-analysis, I2 ≤ 50% was accepted. The Egger’s test was performed using the software Stata version 11.0 (Stata Corp., College Station, TX, USA), with a significance level of α = 0.05.

3. Results

3.1. Literature Search

Based on the inclusive criteria and exclusive criteria, all articles were retrieved and carefully reviewed to assess the eligibility. Forty-nine eligible studies were identified after a screening of 1109. The selection of studies for the meta-analysis is shown in Figure 1 [82].

3.2. Characteristics of the Studies

Among the forty-nine studies, the 10 study factors used to pool ORs with 95% CIs were as follows: Injecting drug use (43 studies, 53,860 cases, 69,747 controls); sharing needles and syringes (33 studies, 40,777 cases, 23,361 controls); duration of drug use >5 years (12 studies, 10,282 cases, 8,794 controls); unemployment (6 studies, 8,361 cases, 5,420 controls); sex (male) (39 studies, 57,403 cases, 72,922 controls); education level ≤9 years (29 studies, 46,931 cases, 61,841 controls); sexual behavior without a condom (15 studies, 10,032 cases, 24,156 controls); Han ethnic group (15 studies, 12,014 cases, 16,129 controls); married or cohabiting with a regular partner (26 studies, 46,626 cases, 62,107 controls); commercial sexual behavior (14 studies, 9,698 cases, 28,505 controls). Among the forty-nine studies, the proportion of 4 studies (injecting only) was 8.16%, the proportion of 2 studies (non-injecting) was 4.08%, and the proportion of 43 studies (injecting and non-injecting) was 87.76%.
The characteristics of all studies evaluated in this meta-analysis are shown in Table 1.

3.3. Results of Pooled ORs

In this meta-analysis, the pooled ORs with 95% CIs for study factors were as follows: Injecting drug use 10.11 (8.54, 11.97); sharing needles and syringes 2.24 (1.78, 2.83); duration of drug use >5 years 2.39 (1.54, 3.71); unemployment 1.50 (1.22, 1.85); commercial sexual behavior 1.00 (0.73, 1.38); sex (male) 1.04 (0.91, 1.18); married or cohabiting with a regular partner 0.88 (0.79, 0.98); Han ethnic group 0.94 (0.73, 1.20); sexual behavior without a condom 1.72 (1.07, 2.78); and education level ≤9 years 1.05 (0.92, 1.21).
The pooled ORs with their 95% CIs for study factors are detailed in Figure 2, Figure 3 and Figure 4, and the axes of the figures mean OR = 1.

3.4. Results of Heterogeneity Evaluation

A heterogeneity test showed that variations among studies for the pooled ORs with 95% CIs for factors including injecting drug use, sharing needles and syringes, drug use duration of >5 years, unemployment, commercial sexual behavior, sex (male), married or cohabiting with a regular partner, Han ethnic group, sexual behavior without a condom, and an education level of ≤9 years were statistically significant (p < 0.10). The effects of these factors were then pooled using the random effect model. These results are detailed in Figure 2, Figure 3 and Figure 4.

3.5. Publication Bias

In this meta-analysis, a funnel plot for the duration of drug use was symmetrical, with the axis of symmetry (OR = 1) being to the right of center, as detailed in Figure 5. The results of Egger’s test for study factors were all p > 0.05, as detailed in Table 2.

3.6. Sensitivity Analysis

In view of the reliability of the pooled ORs using the random effect model for terms including injecting drug use, drug use duration of >5 years, unemployment, commercial sexual behavior, sex (male), married or cohabiting with a regular partner, Han ethnic group, sharing needles and syringes, sexual behavior without a condom, and an education level of ≤9 years, we omitted studies with the highest weights, pooled the remaining studies, and acquired the ORweight values with 95% CIs. These pooled values were compared with those obtained before the studies were omitted for qualitative and quantitative comparisons and no major changes in the pooled ORs with 95% CIs were observed for any of the study factors, as detailed in Table 2.

4. Discussion

This study found that drug users with a history of injecting drug use, and/or sharing needles/syringes, drug use duration of >5 years, and/or unemployment, and/or sexual behavior without a condom, were at increased risk of HCV infection, whereas drug users who were married or cohabiting with a regular partner were at decreased risk of developing HCV infection. This study also found that, for drug users (male), commercial sexual behavior, Han ethnicity, an education level of ≤9 years, did not affect the risk of developing HCV infection.
In general, exposure to HCV-contaminated needles and syringes increases the risk of HCV infection, and such exposure may be common among injecting drug users [83,84]. The findings of our meta-analysis confirmed that drug users with histories of injecting drug use were at increased risk of HCV infection, and this result was consistent with those of Xia et al. [26]. However, the findings of this meta-analysis that injecting drug users with a history of sharing needles/syringes were at increased risk of developing HCV infection was not consistent with the results reported in the meta-analysis by Xia et al. in 2008, and this may be related to the fact that only three studies on sharing needles were pooled in Xia et al.’s study and that this small sample size led to low test efficiency and unreliable results [26].
The findings of this meta-analysis also showed that drug use duration of >5 years was a risk factor for developing HCV infection, which may relate to the longer the duration of drug use, the greater the opportunity to be exposed to HCV-contaminated needles or goods, potentially leading to an infection. This result was consistent with the findings of a previous meta-analysis report [26].
In view of that, methadone maintenance treatment can reduce or put an end to risky drug-use behaviors. This discovery suggests methadone maintenance treatment should be scaled up further so as to shorten the duration of drug use and reduce the risk of HCV infections [24].
The findings of this meta-analysis also showed that sexual behavior without a condom was a risk factor for developing HCV infection. The results of the meta-analysis by Xia et al. in 2008′s meta-analysis reported that high-risk sexual practices were strongly associated with injecting drug behavior [26], but the magnitude of high-risk sexual behavior or the correlation between high-risk sexual behavior and drug-injecting behavior and their contribution to the occurrence of HCV infection could not be determined, thus requiring further study. In our study, there was a high proportion of injecting drug behavior and high-risk sexual behavior among the drug users, but related information on individual cases was not available.
The use of amphetamine-type stimulants is currently on the rise, as is unprotected sexual behavior becoming more common and leads to a high prevalence of HCV infection among the club drug user [17,85,86,87], strategies therefore need to be implemented to try to reduce such behaviors and to help to reduce the progression of HCV infection. In addition, further meta-analyses for club drug use will be done when there is enough literature.
The findings of this meta-analysis also showed that unemployment among drug users increased the risk of developing HCV infection, and this finding was consistent with the results of meta-analysis of human immunodeficiency virus (HIV) infection, which has a similar transmission route, among drug users [88].
The findings of our meta-analysis showed that drug users who were married or cohabiting with a regular partner were at decreased risk of developing HCV infection, and this finding was consistent with the results of meta-analysis published by Hagan et al. [27], and this may be related to the fact that these drug users had fewer sexual partners and fewer opportunities to be exposed to HCV-infected bodily fluids. However, the findings of this meta-analysis also showed that drug users with commercial sexual behavior, namely having multiple sexual partners, were not at increased risk of developing HCV infection, and this may be related to using club drug use with a shorter duration of drug use [15], although this requires further investigation.
The findings of this meta-analysis also showed that those of Han ethnicity, compared with those of other minority ethnic groups, were not at increased or decreased risk of developing HCV infection, and this finding was consistent with the results of meta-analysis published by Xia et al. [26]. Our findings also showed that drug users with an education level of ≤9 years were not at increased or decreased risk of developing HCV infection; however, this finding was inconsistent with that of a previous meta-analysis of HIV infection, which has a similar transmission route among drug users [88].
The limitations of this study were that even though the ORs of the study factors were pooled using a random–effect method, heterogeneity among studies might have influenced the findings. In addition, some study factors, for example, some racial classifications (white or black) were not available to be pooled. Lastly, few studies could be unavailable because of language limitations, in view of that, this meta-analysis’ publication bias was not statistically significant, and thus, this aspect influenced findings slightly.

5. Conclusions

This study found that drug users with histories of injecting drug use, sharing needles and syringes, drug use duration of >5 years, and unemployment, were confirmed to be at increased risk of HCV infection. Our findings indicate that high-risk drug users should be closely monitored and sterile needles and syringes should be made available to ensure safe injection. In view of that, methadone maintenance treatment can reduce or put an end to risky drug-use behaviors and should be scaled up further so as to shorten the duration of drug use, thereby reducing HCV infection.

Author Contributions

Study design: C.G.H., B.Z., G.F.C., H.K.L., Y.D.C. Statistical analysis and interpretation: H.K.L., Y.D.C. Manuscript preparation: G.F.C., S.F.X., Z.G.J., Z.T.W., Y.D.C. Critical review of manuscript: B.Z., Y.D.C., C.G.H. All authors read and approved the final manuscript.

Funding

This work was supported by National Health and Family Planning Commission of the People’s Republic of China (No. WKJ-ZJ-1917).

Acknowledgments

The authors appreciate the collaboration of staff from our public opinion monitoring and health communication research team.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
HCVHepatitis C Virus
CIConfidence Interval
OROdds Ratio
M-HMantel-Haenszel
WHOWorld Health Organization

References

  1. Li, J.; Chen, J.; Zhuang, H. Epidemiology of Hepatitis C. J. Pract. Liver Dis. 2012, 15, 376–379. [Google Scholar]
  2. WHO. Guidelines for the Screening Care and Treatment of Persons with Hepatitis C Infection; World Health Organization: Geneva, Switzerland, 2003. [Google Scholar]
  3. Falade-Nwulia, O.; Suarez-Cuervo, C.; Nelson, D.R.; Fried, M.W.; Segal, J.B.; Sulkowski, M.S. Oral Direct-Acting Agent Therapy for Hepatitis C Virus Infection: A Systematic Review. Ann. Intern. Med. 2017, 166, 637–648. [Google Scholar] [CrossRef] [PubMed]
  4. Millman, A.J.; Nelson, N.P.; Vellozzi, C. Hepatitis C: Review of the Epidemiology, Clinical Care, and Continued Challenges in the Direct Acting Antiviral Era. Curr. Epidemiol. Rep. 2017, 4, 174–185. [Google Scholar] [CrossRef] [PubMed]
  5. Jakobsen, J.C.; Nielsen, E.E.; Feinberg, J.; Katakam, K.K.; Fobian, K.; Hauser, G.; Poropat, G.; Djurisic, S.; Weiss, K.H.; Bjelakovic, M. Direct-acting antivirals for chronic hepatitis C. Cochrane Database Syst. Rev. 2017. [Google Scholar] [CrossRef] [PubMed]
  6. WHO. Guidelines for the Screening, Care and Treatment of Persons with Hepatitis C Infection. 2014. Available online: https://www.who.int/hepatitis/publications/hepatitis-c-guidelines/en/ (accessed on 20 August 2017).
  7. Jia, Z.S. Review and reflection: 30 years of research on prevention and treatment of hepatitis C. J. Clin. Hepatobiliary Dis. 2015, 31, 1803–1807. [Google Scholar]
  8. Zheng, E.D.; Gao, L.M.; Peng, X.; Xie, T.S.; Liu, H.Y.; Sun, Y.Q.; Huang, J.; Li, H. HIV and HCV infection situation and associated risk factors among injecting drug users: A meta-analysis. Chin. J. Dis. Control. Prev. 2017, 21, 1271–1277. [Google Scholar]
  9. Zhuang, X.; Liang, Y.; Chow, E.P.F.; Wang, Y.F.; Wilson, D.P.; Zhang, L. HIV and HCV prevalence among entrants to methadone treatment clinics in China: A systematic review and meta-analysis. BMC Lnfect. Dis. 2012, 12, 130–134. [Google Scholar] [CrossRef] [PubMed]
  10. Zibbell, J.; Iqbal, K.; Patel, R.; Suryaprasad, A.; Sanders, K.; Moore-Moravian, L.; Serrecchia, J.; Blankenship, S.; Ward, J.; Holtzman, D.; et al. Increases in hepatitis C virus infection related to injection drug use among persons aged ≤30 years-Kentucky, Tennessee, Virginia, and West Virginia, 2006–2012. MMWR Morb. Mortal. Wkly. Rep. 2015, 64, 453–459. [Google Scholar] [PubMed]
  11. United Nations Office on Drugs and Crime. World Drug Report 2017. Available online: http://www.nncc626.com/2018-06/11/c_129892175.htm (accessed on 21 August 2017).
  12. Degenhardt, L.; Copeland, J.; Dillion, P. Recent trends in the use of“club drugs”: All Australian review. Subst. Use Misuse 2005, 40, 1241–1257. [Google Scholar] [CrossRef]
  13. United Nations Officeon Drugs and Crime (UNODC). 2011 Patterns and Trends of Amphetamine-Type Stimulants and Other Drugs: Asia and the Pacific [EB/OL]. (2012-10-18) (2014-12-21). Available online: http://www.unode.org/documents/scientific/Asia_and_the_Pacific_2011_Regional_ATS_Report.pdf (accessed on 25 August 2017).
  14. Fernández, M.; Bowen, G.; Varga, L.; Collazo, J.; Hernandez, N.; Perrino, T.; Rehbein, A. High rates of club drug use and risky sexual practices among Hispanic men who have sex with men in Miami, Florida. Subst. Use Misuse 2005, 40, 1347–1363. [Google Scholar] [CrossRef]
  15. Parsons, J.; Kelly, B.; Wells, B. Difierences in club drug use between heterosexual and lesbian/bisexual females. Addict. Behav. 2006, 31, 2344–2350. [Google Scholar] [CrossRef]
  16. Pan, X.H.; Jiang, J.; He, H.; Chen, L.; Yang, J.Z.; Zhang, H.B.; Wang, N. Survey of prevalence of HIV infection, syphilis and HCV infection and related risk behaviors among club drug users in Zhejiang, 2011. Chin. J. Epidemiol. 2015, 36, 934–11. [Google Scholar]
  17. Liu, H.M. World Drug Report 2004. Available online: http://www.people.com.cn/GB/guandian/183/2281/3276/2607166.htmI (accessed on 23 August 2017).
  18. Legal Daily. Nearly 3 Million Drug Addicts Have Been Registered in China. Available online: http://legal.people.eom.en/n/2015/0619/el88502-27184718.htm (accessed on 19 December 2015).
  19. Puente, M.T.; Cuevas, J.; Jimenez-Hernandez, N.; Bracho, M.; García-Robles, I.; Wrobel, B.; Carnicer, F.; Olmo, J.D.; Ortega, E.; Moya, A.; et al. Genetic variability in hepatitis C virus and its ruIe in antiviral treatment response. J. Viral Hepat. 2008, 15, 188–200. [Google Scholar] [CrossRef] [PubMed]
  20. Tan, Y.; Wei, Q.H.; Chen, L.J.; Chan, P.C.; Lai, W.S.; He, M.L.; Kung, H.F.; Lee, S.S. Molecular epidemiology of HCV monoinfection and HIV/HCV eoinfection in injection drug users in Liuzhou, Southern China. PLoS ONE 2008, 3, e3608. [Google Scholar] [CrossRef] [PubMed]
  21. Yang, Y.; Guan, Q.Z.; Xu, Y.; Chen, S.D.; Wu, B.W. Serum epidemiology of hepatitis c and b virus infection in drug users. Zhonghua Shi Yan He Lin Chuang Bing Du Xue Za Zhi 1999, 13, 247–251. [Google Scholar] [PubMed]
  22. Pang, L.; Mi, G.D.; Wang, C.H.; Luo, W.; Rou, K.M.; Li, J.H.; Wu, Z.Y. Evaluation of first 8 pilot methadone maintenance treatment clinics in China. Zhonghua Shi Yan He Lin Chuang Bing Du Xue Za Zhi 2007, 21, 2–5. [Google Scholar]
  23. Dole, V.P.; Nyswander, M. A medical treatment for diacetylmorphine (heroin) addiction. JAMA 1965, 193, 646. [Google Scholar] [CrossRef]
  24. Wu, Z. Landmark Government Methadone Maintenance Program in Mainland China. In Proceedings of the 15th International AIDS Conference, Bangkok, Thailand, 13 July 2004. [Google Scholar]
  25. Wu, Z. Methadone maintenance program in mainland China: From pilot to scale-up. In Proceedings of the International Conference on the Reduction of Drug Related Harm, Belfast, Northern Ireland, UK, 20 March 2005. [Google Scholar]
  26. Hagan, H.; Pouget, E.R.; Jarlais, D.C.D. Meta-Analysis of HCV Prevention for PWID. JID 2011, 204, 74–83. [Google Scholar] [CrossRef]
  27. Xia, X.; Luo, J.; Bai, J.L.; Yu, R.B. Epidemiology of hepatitis C virus infection among injection drug users in China: Systematic review and meta-analysis. Public Health 2008, 122, 990–1004. [Google Scholar] [CrossRef]
  28. Fill, M.A.; Sizemore, L.A.; Rickles, M.; Cooper, K.C.; Buecker, C.M.; Mullins, H.L.; Hofmeister, M.G.; Abara, W.E.; Foster, M.A.; Asher, A.K.; et al. Epidemiology and risk factors for hepatitis C virus infection in a high-prevalence population. Epidemiol. Infect. 2018, 146, 508–515. [Google Scholar] [CrossRef]
  29. Aisyah, D.N.; Shallcross, L.; Hayward, A.; Aldridge, R.W.; Hemming, S.; Yates, S.; Ferenando, G.; Possas, L.; Garber, E.; Watson, J.M.; et al. Hepatitis C among vulnerable populations: A seroprevalence study of homeless, people who inject drugs and prisoners in London. J. Viral Hepat. 2018, 25, 1260–1270. [Google Scholar] [CrossRef] [PubMed]
  30. Nordén, L.; Lidman, C. Differentiated risk behaviour for HIV and hepatitis among injecting drug users (IDUs). Scand. J. Infect. Dis. 2005, 37, 493–497. [Google Scholar] [CrossRef] [PubMed]
  31. Galperim, B.; Cheinquer, H.; Stein, A.; Fonseca, A.; Lunge, V.; Ikuta, N. Intranasal cocaine use does not appear to be an independent risk factor for HCV infection. Addiction 2004, 99, 497–502. [Google Scholar] [CrossRef] [PubMed]
  32. Maher, L.; Jalaludin, B.; Chant, K.G.; Jayasuriya, R.; Sladden, T.; Kaldor, J.M.; Sargent, P.L. Incidence and risk factors for hepatitis C seroconversion in injecting drug users in Australia. Addiction 2006, 101, 1499–1509. [Google Scholar] [CrossRef]
  33. Wei, D.Y.; Yang, Y.; Ruan, Y.H.; Zeng, G.H.; Han, L.; Liang, S.; Zhang, J.H.; Yin, L.; Zhang, L.; Qin, G.M.; et al. HCV Prevalence and Risk Factors among Drug Users in Xichang County of Sichuan, China. J. Prev. Med. Inf. 2005, 21, 135–140. [Google Scholar]
  34. Sun, Y.; Zhang, Y.; Chen, W.; Guan, L.; Liu, H.; Tan, M.J.; Li, D.Q.; Dai, W.P.; Huang, M.S. Hepatitis C Virus Infection among Drug Users. Occup. Health 2007, 23, 881–884. [Google Scholar]
  35. Yun, C.Y.; Wu, J.C.; Liu, J.C. Investigation on HCV infection and influencing factors among drug users in haikou area. Hainan Med. J. 2016, 27, 1878–1880. [Google Scholar]
  36. Cui, X.L.; Li, Z. Investigation on the infection status of HBV, HCV, HIV and syphilis among 483 drug addicts in baoji city in 2005. Prev. Med. Trib. 2005, 11, 169–171. [Google Scholar]
  37. Stone, J.; Fraser, H.; Lim, A.G.; Walker, J.G.; Ward, Z.; Mac Gregor, L.; Trickey, A.; Abbott, S.; Strathdee, S.A.; Abramovitz, D.; et al. Incarceration history and risk of HIV and hepatitis C virus acquisition among people who inject drugs: A systematic review and meta-analysis. Lancet Infect. Dis. 2018, 18, 1397–1440. [Google Scholar] [CrossRef]
  38. Lin, P.; Fan, Z.F.; Yang, F.; Wu, Z.Y.; Wang, Y.; Liu, Y.Y.; Ming, Z.Q.; Li, W.J.; Luo, W.; Fu, X.B.; et al. Effect evaluation of needle exchange project for community drug users in Guangdong. Chin. J. Prev. Med. 2004, 38, 305–309. [Google Scholar]
  39. Chen, H.; Zhao, X.H.; Liao, K.K.; Zhang, J.Y. Analysis of current situation of HCV infection among drug users in Mianyang City. Chin. J. Health Educ. 2018, 34, 258–261. [Google Scholar]
  40. Wu, Z.Q.; Liu, X.F.; Wang, N.; Yang, X.T.; Cao, G.W. Seroprevalence of human immunodeficiency virus, hepatitis c virus, and syphilis infection their influencing factors among drug users in baoshan district of Shanghai from 2010 to 2016. Shanghai J. Prev. Med. 2018, 30, 223–229. [Google Scholar]
  41. Jin, J.; Luo, Y.; Chen, J.F.; Li, X.T.; Zhang, X.L.; Xu, K. Prevalence of HIV, syphilis and HCV and their risk factors among drug users in Hangzhou. Prev. Med. 2018, 30, 248–257. [Google Scholar]
  42. Xian, X.W.; Tong, Z.W.; Rui, G.; Qian, Z.Q. analysis on the status of syphilis and HCV infection and influencing factors among community drug addicts in Jiaxing City. Prev. Med. 2017, 29, 135–139. [Google Scholar]
  43. Ye, Y.; Zhang, Z.; Zhao, X.L.; Tian, T.; Cai, A.; Dai, J. HIV, HCV, syphilis and their co-infection and risk factors analysis among drug users in Urumqi from 2010 to 2014. J. Xinjiang Med. Univ. 2016, 39, 1447–1452. [Google Scholar]
  44. Li, Z.; Liu, J.Z.; Shen, Y.Y. Investigation on the Infection of HIV, HCV and Association High Risk Factors among Drug Users. J. Dali Univ. 2016, 1, 77–81. [Google Scholar]
  45. Tao, Y.X.; Zhao, C.; Gao, X.Y. ChengCurrent situation and influencing factors of HCV infection among drug users in xining city. Guangxi Med. J. 2018, 40, 2855–2858. [Google Scholar]
  46. Zhang, T.; Ji, J.F.; Qiu, Y.W. Analysis of monitoring results of AIDS, syphilis and hepatitis c among drug addicts. Zhejiang Prev. Med. 2012, 24, 29–32. [Google Scholar]
  47. Shen, H.D.; Tang, J.F.; Yang, W.; Zhao, Y. Investigation and analysis of HCV infection among methadone patients in jining county. Soft Sci. Health 2011, 25, 867–870. [Google Scholar]
  48. Liu, Q. Prevalence of HCV, HIV and Syphilis Infection among Drug Addicts at the Methadone Treatment Clinic in Wuhan and Analysis of Risk Factors. Chin. J. Rehabil. 2011, 26, 356–358. [Google Scholar]
  49. Oliveira-Filho, A.B.; Sawada, L.; Pinto, L.C.; Locks, D.; Bahia, S.L.; Castro, J.A.A.; Hermes, R.B.; Brasil-Costa, I.; Amaral, C.E.M.; Lemos, J.A.R. Epidemiological aspects of HCV infection in non-injecting drug users in the Brazilian state of Pará, eastern Amazon. Virol. J. 2014, 11, 38–46. [Google Scholar] [CrossRef] [PubMed]
  50. Wei, X.L.; Wang, L.R.; Wang, X.L.; Li, J.S.; Li, H.X.; Jia, W. Risk Factors of Hepatitis C Virus Infection in Drug Users from Eleven Methadone Maintenance Treatment Clinics in Xi’an, China. Hepat. Mon. 2014, 14, e19061. [Google Scholar] [CrossRef] [PubMed]
  51. Zeremski, M.; Makeyeva, J.; Arasteh, K.; Jarlais, D.C.D.; Talal, A.H. Hepatitis C virus-specific immune responses in noninjecting drug users. J. Viral Hepat. 2012, 19, 554–559. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Keen, L., II; Khan, M.; Clifford, L.; Harrell, P.T.; Latimer, W.W. Injection and non-injection drug use and infectious disease in Baltimore City: Differences by race. Addict. Behav. 2014, 39, 1325–1333. [Google Scholar] [CrossRef] [PubMed]
  53. Iversen, J.; Wand, H.; Gonnermann, A.; Maher, L.; On Behalf of the Collaboration of Australian Needle and Syringe Programs. Gender differences in hepatitis C antibody prevalence and risk behaviours amongst people who inject drugs in Australia 1998–2008. Int. J. Drug Policy 2010, 21, 471–477. [Google Scholar] [CrossRef]
  54. Demetriou, V.L.; van de Vijver, D.A.; Hezka, J.; Kostrikis, L.G.; Cyprus IVDU Network. Hepatitis C Infection Among Intravenous Drug Users Attending Therapy Programs in Cyprus. J. Med Virol. 2010, 82, 263–271. [Google Scholar] [CrossRef] [PubMed]
  55. Shi, P.; Li, L. Survey and analysis on the HCV infection among drug users. Jiangsu Prev. Med. 2009, 20, 10–13. [Google Scholar]
  56. Fan, L.J. Analysis of HIV, HCV and syphilis infection among 250 drug addicts in pingnan county. Health Heaven. Earth-Health Insp. Prev. 2010, 4, 113–115. [Google Scholar]
  57. Qin, T.X. Results Analysis of HIV Sentinel Surveillance among Drug Addicts in Detention in Nanchang Area. Occup. Health 2011, 27, 2180–2184. [Google Scholar]
  58. Liu, H.B.; Zhe, X.L. Study on HCV Co-infection in Yulin Drug Users. J. Med. Pest. Control. 2010, 26, 731–733. [Google Scholar]
  59. Li, G.Q.; Wu, M.Q.; Yuan, S.R. Analysis of HBV, HCV infection and liver function in 249 cases of heroin addicts. Chin. J. Drug Abuse Prev. Treat. 2009, 15, 80–84. [Google Scholar]
  60. Huang, D.P.; Li, Y.J.; Zhou, Y.Y.; Guan, H.J. Prevalence of HCV infection and related risk factors among drug users in Changde City. Pract. Prev. Med. 2017, 24, 330–332. [Google Scholar]
  61. Yang, K.; Yang, Y.L.; Peng, G.P.; Jiang, H.L.; Li, L.L.; Tang, H. Analysis of HIV, HCV and TP Infection in Patients under Maintenance Treatment Methadone with in Yichang Urban City. Chin. J. Derm. Venereol. 2018, 32, 302–306. [Google Scholar]
  62. Chen, L.; Lin, X.; Lian, Q.L.; Zhang, M.Y.; Zheng, W.X. HCV infection and related factors among drug users in Fujian Province, 2010–2015. Chin. J. AIDS STD 2018, 24, 48–52. [Google Scholar]
  63. Tang, R.H.; Gao, Y.; Yang, Y.C.; Cao, Y.F.; Yang, S.J.; Ye, R.H.; Wang, J.B.; Wang, Y.K.; Duan, S.; He, N. Analysis of HCV infection rate and its influence factors among drug users in Dehong Prefecture, Yunnan Province. Chin. J. Prev. Med. 2018, 52, 87–91. [Google Scholar]
  64. Guo, Y.; Ning, T.L.; Zhou, N. HCV inaction status and associated factors among drug users in Tianjin from 2011 to 2015. Int. J. Virol. 2017, 24, 178–184. [Google Scholar]
  65. Li, N.; Wang, X.W.; Nie, Y.G.; Ma, Y.M.; Wen, J.; Fan, P.Y.; Sun, D.Y.; Zhu, Q. HCV infeetion status and related risk factors in drug users under HIV sentinel surveillance in Henan province, 2011–2015. Chin. J. Epidemiol. 2016, 37, 821–826. [Google Scholar]
  66. Huang, X.M.; Lin, P.; Li, Y.; Fu, X.B. Analysis on HCV seroprevalence and related risk factors among drug users, Guangdong province, 2011—2013. Prev. Med. Trib. 2016, 22, 88–94. [Google Scholar]
  67. Yao, Z.Z.; Xu, X.R.; Lei, L.J. Investigation and analysis of hepatitis c infection among drug users in usu city. Bull. Dis. Control. Prev. 2015, 30, 3–9. [Google Scholar]
  68. Wei, L.; Zhang, Y.J. Prevalence and associated risk factors of HIV, HCV and TP in drug users in Liuzhou City. Chin. J. Dis. Control. Prev. 2015, 19, 1248–1253. [Google Scholar]
  69. Jin, H.Y.; Li, W.T.; Yan, L.; Fu, X.Y.; Xu, M.M.; Pu, S.D.; Liu, X.J.; He, J.C. Analysis of infection of HBV, HCV and TP and relative factors among drug addicts under compulsory rehabilitation in Lanzhou. J. Lanzhou Univ. (Med. Sci.) 2015, 41, 44–49. [Google Scholar]
  70. Ma, J.X.; Liu, S.J.; Wang, Y.B.; Yang, C. Analysis of hepatitis c infection and its influencing factors among methadone addicts in baiyin outpatient clinic. Chin. J. PHM 2014, 30, 531–533. [Google Scholar]
  71. Pu, L.F.; Su, Y.Y.; Wang, G.X.; Bai, J. Prevalence of HIV and HCV infections in patients receiving methadone maintenance treatment in Kaiyuan. Chin. J. Epidemiol. 2015, 36, 29–32. [Google Scholar]
  72. Li, F.; Wang, H. s.; Liu, H.X.; Guo, S.Y.; Hao, Z. Hepatitis C infection and its influencing factors among drug users in Changping district of Beij ing in 2009–2013. Chin. Prev. Med. 2015, 16, 105–108. [Google Scholar]
  73. Han, X.; Hou, X.Y.; Li, H.J. The present situation of AIDS, syphilis and hepatitis c among drug users in Hohhot in 2011. J. Dis. Surveill. Control. 2014, 8, 494–496. [Google Scholar]
  74. Feng, Y.J.; Wang, L.; Liang, L.; Cao, N.X. The Infectious Status of HIV, HCV and Treponema pallidum Infection and Related Risk Factor in 636 Drug Users in Qinhuangdao City. Chin. J. Derm. Venereol. 2014, 18, 600–604. [Google Scholar]
  75. Huang, D.S.; Zheng, W.B.; Yang, J.F.; Li, Y.P.; Hu, A.Y.; Guo, J.H.; Peng, J.Y.; Xu, Z.C.; Liu, L.; Ding, Y.; et al. Analysis of HCV ser0preVaIence and related influencing factors among drug users in HIV sentinel points, Baoshan City. Chin. J. AIDS STD 2013, 19, 279–283. [Google Scholar]
  76. Zhao, H.; Ban, H.; Gao, L. Investigation on infection of hepatitis C virus among IDUs in Wuhai City from 2010 to 2011. J. Dis. Monit. Control. 2012, 6, 705–707. [Google Scholar]
  77. Shi, W.Y.; Xie, Y.Y.; Liu, C. An epidemiological survey On hepatitis C virus infection among drug users in Beijing. Chin. J. AIDS STD 2012, 18, 184–188. [Google Scholar]
  78. Zhong, H.R. Analysis of HIV, HCV and syphilis infection in 296 drug addicts in ganzhou city. South China J. Prev. Med. 2010, 36, 31–33. [Google Scholar]
  79. National Health and Family Planning Commission of the People’s Republic of China. WS 213–018 Diagnosis for hepatitis C. J. Clin. Hepatol. 2018, 34, 3–6. [Google Scholar]
  80. Ebrahim, S.; Clarke, M. STROBE: New standards for reporting observational epidemiology, a chance to improve. Intern. J. Epidemiol. 2007, 36, 946–949. [Google Scholar] [CrossRef] [PubMed]
  81. Strobe Statement: Strengthening the Reporting of Observational Studies in Epidemiology [EB/OL]. Available online: http://www.strobe-statement.org/index.php?id=strobe-translations (accessed on 1 May 2013).
  82. Ades, A.E.; Lu, G.; Higgins, J.P. The interpretation of random-effects meta-analysis in decision models. Med. Decis. Mak. 2005, 25, 646–654. [Google Scholar] [CrossRef]
  83. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; The PRISMA Group. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef]
  84. Schaefer, M.; Mauss, S. Hepatitis C treatment in patients with drug addiction: Clinical management of interferon-alpha-associated psychiatric side effects. Curr. Drug Abus. Rev. 2008, 1, 177–188. [Google Scholar] [CrossRef]
  85. Dolan, K.A.; Shearer, J.; White, B.; Zhou, J.; Kaldor, J.; Wodak, A.D. Four-year follow-up of imprisoned male heroin users and methadone treatment:mortality, re-incarceration and hepatitis C infection. Addiction 2005, 100, 820–829. [Google Scholar] [CrossRef] [PubMed]
  86. Hao, W.; Xiao, S.; Liu, T.; Young, D.; Chen, S.; Zhang, D.; Li, C.; Shi, J.; Chen, G.; Yang, K. The second National Epidemiological Survey on illicit drug use at six high-prevalence areas in China: Prevalence rates and use patterns. Addiction 2002, 97, 1305–1316. [Google Scholar] [CrossRef]
  87. Zhao, M.; Du, J.; Lu, G.H.; Wang, Q.Y.; Xu, H.; Zhu, M.; McCoy, C.B. HIV sexual risk behaviors among injection drug users in Shanghai. Drug Alcohol Depend. 2006, 82 (Suppl. S1), s43–s48. [Google Scholar] [CrossRef]
  88. Xing, J.N.; Qian, S.S.; Guo, W.; Li, Y.G.; Ding, Z.W.; Wang, L. Meta-analysis on risk factors of HIV infection among drug users in China. Dis. Surveill. 2013, 28, 823–828. [Google Scholar]
Ijerph 16 02345 g001 550
Figure 1. A flow chart of the studies selection process.
Figure 1. A flow chart of the studies selection process.
Ijerph 16 02345 g001
Ijerph 16 02345 g002 550
Figure 2. Effects of pooled ORs for factors correlating to the development of HCV infection among drug users ((A) sexual behavior without a condom; and (B) married or cohabiting with a regular partner).
Figure 2. Effects of pooled ORs for factors correlating to the development of HCV infection among drug users ((A) sexual behavior without a condom; and (B) married or cohabiting with a regular partner).
Ijerph 16 02345 g002
Ijerph 16 02345 g003 550
Figure 3. Effects of pooled ORs for factors correlating to the development of HCV infection among drug users ((C) Sharing needles and syringes; and (D) Duration of drug use >5 years).
Figure 3. Effects of pooled ORs for factors correlating to the development of HCV infection among drug users ((C) Sharing needles and syringes; and (D) Duration of drug use >5 years).
Ijerph 16 02345 g003
Ijerph 16 02345 g004 550
Figure 4. Effects of pooled ORs for injecting drug use correlating to the development of HCV infection among drug users.
Figure 4. Effects of pooled ORs for injecting drug use correlating to the development of HCV infection among drug users.
Ijerph 16 02345 g004
Ijerph 16 02345 g005 550
Figure 5. A funnel plot of the articles publication for the duration of drug use.
Figure 5. A funnel plot of the articles publication for the duration of drug use.
Ijerph 16 02345 g005
Table
Table 1. Characteristics of the studies.
Table 1. Characteristics of the studies.
Reference NumberAuthorYear of PublicationRegionsType of Drug UseParticipants Category (Case/Control)Sample Size (Case/Control)Male/FemaleAge (Years) *
[38]Chen Hua2018Sichuan, Mianyanginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1829; 9772016; 79039.0 ± 7. 5
[39]Wu Zhen Xiang2018Shanghai, Baoshaninjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1199; 16042138; 66539.7 ± 9.86
[40]Jin Jie2018Zhejiang, Hangzhouinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses923; 31443329; 63836.33 ± 8.98
[41]Xu Wen Xin2017Zhejiang, Jiaxinginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses51; 398356; 9327.50 ± 12.28
[42]Ye.y2016Xinjiang, Wulumujiinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses745; 9791 679; 4935–45
[35]Yun Chang Yan2016Yunnan, Haikeinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses823; 786-33.8 ± 4.8
[43]Li Ze2016Yunnan, Daliinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses196; 227400; 2315–62
[44]Tao Yi Xin2018Qinghai, Xininginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses207; 456401; 262>20
[45]Zhang Tao2012Zhejiang, Jinhuainjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses145; 255331; 6931.61 ± 6.80
[46]Shen Han Ding2011Yunnan, Jinninginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses273; 48290; 3120–78
[47]Liu Qun2011Hubei, Wuhaninjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1156; 1841000; 34032.5 ± 6.2
[30]Bruno Galperim2004Porto Alegre, RS, Brazilinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses15; 4550; 1031 ± 7
[31]Lisa Maher2006Sydney, Australiainjecting onlyHCV-infected drug uses/non-HCV-infected drug uses68; 300140; 228>15
[48]Aldemir B. Oliveira-Filho2014Pará, Brazilnon-injectingHCV-infected drug uses/non-HCV-infected drug uses106; 194191; 10932.5 ± 10.3
[49]Wei Xiaoli2014Shanxi, Xianinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses5940; 43038653; 159037.4 ± 6.7
[50]M. Zeremski2012New York, USAnon-injectingHCV-infected drug uses/non-HCV-infected drug uses11; 4648; 944 ± 7
[51]Larry Keen II2014Florida, USAinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses274; 208 284; 19832.66 ± 7.01
[52]Jenny Iversen2010New South Wales, Australiainjecting onlyHCV-infected drug uses/non-HCV-infected drug uses8100; 748310162; 542131 ± 8.8
[53]Victoria L. Demetriou2010Nicosia, Cyprusinjecting onlyHCV-infected drug uses/non-HCV-infected drug uses19; 2235; 627 (25–31)
[27]Fill MA2018Tennessee, USAinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses571; 82166:100>18
[28]D. N. Aisyah2017London, UKinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses119; 4221093; 110>18
[29]Lillebil Norden 2005Huddinge, Swedeninjecting onlyHCV-infected drug uses/non-HCV-infected drug uses37; 528; 14-
[74]Huang Dong Sheng2013Yunnan, Baoshaninjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses404; 498874; 28-
[75]Zhao Hong2012Neimenggu, Wuhaiinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses580; 331856; 5518–63
[35]Cui Xiu Ling2005Shanxi, Baojiinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses23; 460427; 5619–52
[76]Shi Wen Ya2012Beijing, Fengtaiinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses347; 906954; 299-
[77]Zhong Hai Rong2010Jiangxi, Ganzhouinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses106; 190237; 5916–51
[32]Wei Da Yin2005Sichuan, Liangshaninjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses346; 273519; 10028.9 ± 6.4
[33]Sun Yan2007Hunan, Changshainjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses662; 110452; 32015–53
[54]Shi Ping2009Jiangsu, Nanjinginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses957; 18542305; 50618–74
[55]Fan Lin Jun2010Guangxi, Pingnaninjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses203; 47245; 537 (15–68)
[56]Tang Xue Qin2011Jiangxi, Nanchanginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses233; 567768; 3218–77
[57]Liu Hui Bin2010Shanxi, Yulininjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses352; 125440; 3720–52
[58]Li Guang Qing2009Hunan, Bingzhouinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses184; 65185; 6432.32 (17–54)
[59]Huang Dao Ping2017Hunan, Changdeinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1098; 9021868; 13233 (16–63)
[60]Yang Kai2018Hubei, Yichanginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1523; 2881411; 40044.78 ± 6.91
[61]Chen Liang2018Fujian, Fuqinginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses3124; 43926630; 88635.37 ± 8.97
[62]Tang Ren Hai2018Yunnan, Dehonginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1369; 61617176; 35435.14 ± 10.9
[63]Guo Yan2017Tianjiin, Chinainjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses1039; 9611642; 35833 (34.5 ± 8.69)
[64]Li Nin2016Henan, Chinainjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses760; 13,19511,224; 272437.32 ± 8.43
[65]Huang Xi Ming2016Guangdong, Chinainjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses24,877; 21,65243,108; 3421-
[66]Yao Zhong Zheng2015Xinjiang, Wushiinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses132; 182229; 1519–69
[67]Wei Li2015Guangxi, Liuzhouinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses276; 124296; 104-
[68]Jin Hui Ya2015Gansu, Lanzhouinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses41; 189120; 11039.7–9.1
[69]Ma Ji Xiong2014Gansu, Baiyinginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses82; 506548; 4030.06 ± 6.3
[70]Pu Li Fang2015Yunnan, Kaiyuaninjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses239; 36209; 6641.6 ± 6.0
[71]Li Feng2015Beeijing, Changpinginjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses139; 472504; 107>20
[72]Han Xia2014Neimenggu, Huhehaoteinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses52; 191243; 0>20
[73]Feng Yan Jie2014Hebei, Qinhuangdaoinjecting and non-injectingHCV-infected drug uses/non-HCV-infected drug uses332; 304577; 59>20
Note: *: mean ± standard deviation; mean (minimum–maximum); minimum–maximum; mean.
Table
Table 2. The subgroup characteristics of the study factors associated with HCV infection among drug users after omitting the studies with the maximum weight value for the ORs in the subgroup analysis and the results of Egger’s test.
Table 2. The subgroup characteristics of the study factors associated with HCV infection among drug users after omitting the studies with the maximum weight value for the ORs in the subgroup analysis and the results of Egger’s test.
Subgroup Analyses by Study Factors (1) *Pooled OR with 95% CI before Reference Omitted (2)Pooled OR with 95% CI after Reference Omitted (3)Qualitative Comparison: Reversal of Pooled OR with 95% CI ((2) and (3) Compared)Quantitative Comparison: Similar Values of Pooled OR with 95% CI ((2) and (3) Compared)Reference OmittedEgger’s Test
tp-Value
Education level ≤9 years1.05 (0.92, 1.21)1.05 (0.91, 1.21)NoYes[49]−0.770.450
Sexual behavior without a condom1.72 (1.07, 2.78)1.50 (1.10, 2.03)NoYes[65]−1.790.097
Sharing needles and syringes2.244 (1.78, 2.83)2.31 (1.66, 3.23)NoYes[65,67]0.860.395
Han ethnic group0.94 (0.73, 1.20)0.96 (0.70, 1.30)NoYes[62]0.270.788
Married or cohabiting with a regular partner0.88 (0.79, 0.98)0.87 (0.78, 0.97)NoYes[65]−1.530.139
Sex (male)1.04 (0.91, 1.18)1.02 (0.90, 1.15)NoYes[52,65]−1.010.319
Commercial sexual behavior1.00 (0.73, 1.38)0.95 (0.61, 1.47)NoYes[39,40,64]−0.790.446
Unemployment1.50 (1.22, 1.85)1.48 (1.07, 2.06)NoYes[49]−0.230.831
Duration of drug use >5 years3.49 (3.24, 3.75)3.47 (3.22, 3.74)NoYes[58]−1.780.106
Injecting drug use10.11 (8.54, 11.97)10.21 (8.03, 12.97)NoYes[49,61,65]−0.350.731
Note: *: (1)—means Subgroup Analyses by Study Factors; (2)—means Pooled OR with 95% CI before Reference Omitted; (3)—means Pooled OR with 95% CI after Reference Omitted.

Share and Cite

MDPI and ACS Style

Zhou, B.; Cai, G.F.F.; Lv, H.K.K.; Xu, S.F.F.; Wang, Z.T.T.; Jiang, Z.G.G.; Hu, C.G.G.; Chen, Y.D.D. Factors Correlating to the Development of Hepatitis C Virus Infection among Drug Users—Findings from a Systematic Review and Meta-Analysis. Int. J. Environ. Res. Public Health 2019, 16, 2345. https://doi.org/10.3390/ijerph16132345

AMA Style

Zhou B, Cai GFF, Lv HKK, Xu SFF, Wang ZTT, Jiang ZGG, Hu CGG, Chen YDD. Factors Correlating to the Development of Hepatitis C Virus Infection among Drug Users—Findings from a Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health. 2019; 16(13):2345. https://doi.org/10.3390/ijerph16132345

Chicago/Turabian Style

Zhou, Biao, Gao Feng Feng Cai, Hua Kun Kun Lv, Shuang Fei Fei Xu, Zheng Ting Ting Wang, Zheng Gang Gang Jiang, Chong Gao Gao Hu, and Yong Di Di Chen. 2019. "Factors Correlating to the Development of Hepatitis C Virus Infection among Drug Users—Findings from a Systematic Review and Meta-Analysis" International Journal of Environmental Research and Public Health 16, no. 13: 2345. https://doi.org/10.3390/ijerph16132345

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop