ORIGINAL ARTICLE
Year : 2020 | Volume
: 64 | Issue : 5 | Page : 61--66
Factors associated with human immunodeficiency virus infection and self-assessed risk to human immunodeficiency virus among injecting drug users in Manipur, India
Balasubramanian Ganesh1, Kriina Mosoniro2, Joshua Vasna3, Arumugam Elangovan4, Aridoss Santhakumar3, Rajan Shobini5,
1 Scientist D, Laboratory, HIV Surveillance, Chennai, India
2 MSc Scholar, Bio-Statistics, HIV Surveillance, Chennai, India
3 Scientist C, HIV Surveillance, Chennai, India
4 Scientist G, Department of Computing and Information Science, ICMR-National Institute of Epidemiology, Chennai, India
5 Assistant Director General, Strategic Information and Surveillance, National AIDS Control Organization, Ministry of Health Family Welfare, Government of India, New Delhi, India
Correspondence Address:
Dr. Rajan Shobini
National AIDS Control Organization, Ministry of Health Family Welfare, Government of India, 36 Janpath Road, New Delhi - 110 001
India
Abstract
Background: The proximity of Northeast India to the Golden Triangle facilitates easy accessibility to illicit drugs, resulting in a higher proportion of injecting drug users (IDUs) in the states of Northeast India. The estimated human immunodeficiency virus (HIV) prevalence among IDU in Manipur which is 1.43% is higher than that of the national figure. Objectives: The objectives of the study were to find the factors associated with HIV infection and correlate the association between HIV status and self-assessed risk to HIV among IDUs in Manipur. Methods: National Integrated Biological and Behavioral Surveillance (2014–2015) data were used for the study; all analyses done were weighted. In Manipur, information was collected from 1594 IDUs during the surveillance between 2014 and 2015 across four domains, namely Chandel (396), Imphal East (397), Thoubal (401), and Senapati (400). Chi-square test was performed to test the association between the independent and dependent variables. Multivariable logistic regression was performed to identify risk factors associated with HIV positivity. Results: Higher age, unsafe injecting practice, low education status, and low-income status were significantly (P < 0.05) associated with HIV infection among IDUs in Manipur. Self-assessed risk of HIV infection by IDU was significantly associated with HIV positivity. Conclusion: Interventions among IDUs in Manipur should focus on emphasizing safe injecting practices along with creating awareness on HIV prevention and management.
How to cite this article:
Ganesh B, Mosoniro K, Vasna J, Elangovan A, Santhakumar A, Shobini R. Factors associated with human immunodeficiency virus infection and self-assessed risk to human immunodeficiency virus among injecting drug users in Manipur, India.Indian J Public Health 2020;64:61-66
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How to cite this URL:
Ganesh B, Mosoniro K, Vasna J, Elangovan A, Santhakumar A, Shobini R. Factors associated with human immunodeficiency virus infection and self-assessed risk to human immunodeficiency virus among injecting drug users in Manipur, India. Indian J Public Health [serial online] 2020 [cited 2023 Apr 2 ];64:61-66
Available from: https://www.ijph.in/text.asp?2020/64/5/61/282418 |
Full Text
Introduction
Human immunodeficiency virus (HIV) is a virus that infects the cells of the immune system, destroys, and impairs its functions, causing the acquired immunodeficiency syndrome (AIDS). The main routes of HIV transmission are unprotected sex with HIV-infected partners, sharing syringes or needles with an HIV-infected partner, and through HIV-infected mother to newborn. Transmissions through blood transfusion and other routes occur rarely. According to the WHO, more than 75 million people have been infected with HIV virus and about 32 million people have died of HIV worldwide since the beginning of the epidemic.[1] In 2018, approximately 37.9 million people were reported to be living with Human immunodeficiency virus (PLHIV) worldwide.[2] Adult HIV prevalence (15–49 age group) in India was estimated as 0.22%, and the estimated PLHIV in India was 21.40 lakhs in 2017.[3] The “Golden Triangle,” which comprises the Myanmar, Thailand, and Laos, and the Yunnan Province of China, is known to be the world's most prominent source of illicit heroin and opium. Manipur lies closer to these regions and shares a long international border with Myanmar. Heroin is being illegally transited from Thamu, a Burmese town into the Moreh town of Manipur, and transported to the Northeastern states of India via NH 39.[4] Manipur shows 1.43%-estimated adult HIV prevalence among 15–49 years, which is higher than the national average.[5]
IDU contributes to approximately 10% of HIV/AIDS cases worldwide. In India, HIV epidemic is driven by high-risk groups (HRGs) who engage in high-risk behaviors. According to the national Integrated Biological and Behavioral Surveillance (IBBS) 2014–2015 report, HIV prevalence among the core HRG subgroups is as follows: 2.2% in female sex worker, 4.3% in men who have sex with men, 7.2% in transgender, and 9.9% in injecting drug users (IDUs). Apart from HRGs, long-distance truckers (HIV prevalence of 2.59%) and migrant workers (HIV prevalence of 0.99%) also play a vital role in disease transmission.[5] In Manipur, HIV transmission is majorly driven through the injection drug users (IDUs), and IDU-HIV prevalence in Manipur is highest among other states in India. In 2017, Manipur was the second-highest HIV prevalent state in India. Currently, there is not enough documentation on self-assessed risk of HIV infection among the IDUs in Manipur. Hence, identifying the factors and the degree of risk perception associated with HIV prevalence may be helpful for further HIV interventions. The present analysis was carried out with the objectives of finding the factors associated with HIV infection and correlating the association between HIV status and self-assessed risk to HIV among IDUs in Manipur state.
Materials and Methods
Study type and area
National AIDS Control Organization's Institutional Ethics Committee has reviewed and approved the IBBS in India. Data from the IBBS conducted during 2014–2015 were used for the secondary analysis. The survey used probability-based study design for behavioral and biological indicators. The basic unit for the survey was a domain, a continuous geographical unit that represented each HRG. The study population for this study was IDUs from four domains in Chandel, Imphal East, Thoubal, and Senapati. Face-to-face interview by trained personnel was conducted with computer-assisted personal interview tool to collect the data. Nearly 45 min to an hour was taken to complete each interview.
National IBBS is the first nationwide community-based bio-behavioral surveillance among HRG and bridge population, which collected information on many key parameters of programmatic importance. It included indicators related to HIV/AIDS knowledge, HIV prevention, Sexually Transmitted Infections (STI), condom, risk profile and practices, HIV testing, stigma and discrimination as well as exposure to HIV/AIDS services.
Study population and sampling
All men, aged ≥15 years, who had used any psychotropic (addictive/mind altering) substance or drug for recreational or nonmedical reasons through injections, at least once in the past 3 months were included in the survey. The response rate among the IDUs in the IBBS was 90%. In Manipur, 1594 IDUs were recruited from four domains.
The sampling unit in Manipur state had four domains comprising individual and composite districts. The respondents were recruited through a two-stage cluster sampling procedure. Time–location cluster sampling (TLCS) was used to recruit the mobile HRGs from time–location cluster (TLC). Each hotspot was made into four clusters based on high-risk people availability, called peak day-peak time (peak days of operations, maximum HRGs found in particular time), peak days-lean time (peak days of operations, minimum HRGs found in particular time), lean day-peak time (lean days of operations, maximum HRGs found in particular time), and lean day-lean time (lean days of operations, minimum HRGs found in a particular time). The TLCs were selected by systematic random sampling (without replacement) by probability proportional to the estimated measure of size of IDUs. The methodology, laboratory process, weighting procedures, ethical issues, and consent process were followed as per the guidelines, as described elsewhere.[5]
Variables and measurement
Independent variables
Sociodemographic, behavioral, and biological indicators that are highly associated with the risk of HIV infection were studied. These variables included age, marital status, education, occupation, living with a spouse, injecting practices, sexual practice, knowledge, number of times of injected during the last act of injection, most commonplace of injection over the past 3 months, and any STI symptoms during the past 12 months.
Dependent variables
Dependent variables included (a) HIV status (positive and negative) and (b) self-assessed risk to HIV (at least some risk and no risk).
Self-assessed risk was categorized into two groups: any IDU who report himself to be at some risk of being infected with HIV/AIDS was considered as self-assessed to be at risk and as self-assessed to be at no risk, if reported otherwise.
Sexual practice
Sexual practice variable was categorized into “safe” and “at least one unsafe practice,” if the respondent had sex/anal sex and the answers to the questions pertaining to sexual practice were reported “no,” he was categorized as IDU with “at least one unsafe sex practice” else as IDU with “safe sex practice.”
Injection practice
Injection practice was categorized into two, i.e., “safe practice” and “at least one unsafe practice,” if any of the questions on injection practice were answered “yes,” he was categorized into “at least one unsafe practice” else “safe.”
Knowledge
Twelve questions on prevention and transmission were accounted. Based on the number of correct answers, the respondents were classified into two categories: respondents with up to 10 correct answers are defined as “some knowledge” and more than 10 correct answers are defined as “satisfactory knowledge.”
Statistical analysis
The social, demographic, behavioral, and biological indicators were used in a multivariable logistic regression model to predict the probability of HIV prevalence among IDUs. All analysess was weighted. Chi-square test was used to find the association between the independent and dependent variables. All variables significant with P < 0.20 in the unadjusted logistic regression analysis were considered for multivariable logistic regression. Following the selection of significant variables, the suitability of the model fit was assessed using the Hosmer–Lemeshow test with the significance level of 10%. P < 0.05 was used to indicate statistical significance.[6],[7] The model was assessed for confounding, interaction, and multicollinearity. Multicollinearity between independent variables for ordinal was checked with Spearman's rank correlation, and for nominal variables, it was checked with Phi and Cramer's V. Independent variables such as “marital status,” “Injecting place,” and “Number of times injected during the last injection act” were excluded in the final model after Chi-square test and univariate logistic regression were done. Multivariable logistic regression was performed by adjusting the effects of other factors to identify factors associated with HIV infection. Enter method was used for the analysis. Chi-square test was used to find the association for HIV status and self-assessed risk to HIV. Data were analyzed using IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp.
Results
Data collected and the prevalence of HIV among IDUs are presented in [Table 1]. Chandel had the highest HIV prevalence (23.29%), followed by Imphal East (11.39%), Thoubal (10.98%), and Senapati (9.20%). Of the total 1594 samples, 193 (12.1%) were HIV positive.{Table 1}
A majority of the IDUs in Manipur were laborers (57.69%), followed by students or unemployed (26.87%), and other services (15.51%). The highest number of IDUs was aged between 27 and 38 years in all the four districts. About half of the IDUs had secondary level education (51.48%), i.e. class 1–10, 29.82% had higher secondary level education, 15.69% were graduates or higher, while 3.08% of them had received no formal education. During the survey, 61.96% of the IDUs were living with their family/relatives without a sexual partner, 29.32% were living with their spouse, 4.5% were living with a sexual partner other than spouse, and 4.14% were living alone or with friends. The self-reported IDUs were currently suffering from at least one of the STI symptoms (11.30%) such as genital ulcer/sore (ulcer on the penis), urethral discharge (discharge of pus while urinating), and genital warts. Nearly 63.78% (1016) had satisfactory knowledge on HIV prevention and transmission. During the last act of drug injection, 571 (35.84%) reported injecting thrice or more, 635 (39.86%) reported injecting twice, and 387 (24.29%) reported injecting only once. The most commonplace of injection, in the past 3 months, was at drug dealer or peddlers place, i.e. 869 (54.55%), followed by their own house or a friend's house (320, 20.09%).
Factors associated with human immunodeficiency virus infection
Sociodemographic and human immunodeficiency virus
Factors significantly associated with higher risk of infection were unemployment (adjusted odds ratio [AOR] =2.07, 95% confidence interval [CI]: 1.09–3.93), higher age (AOR = 5.12, 95% CI: 3.12–8.41), and low education levels (AOR = 2.10, 95% CI: 1.20–3.69). Within the employed IDUs, laborers/manual workers (AOR = 1.83, 95% CI: 1.05–3.20) were comparatively at a significantly higher risk of infections than the service sector employees.
STI, sexual practice, and human immunodeficiency virus
The presence of STI symptoms and safe or unsafe sexual practices were not associated with the risk of HIV infection. Surprisingly, a reverse association was observed between the presence of STI symptoms and HIV prevalence (AOR = 0.53, 95% CI: 0.29–0.98).
Injecting practice and human immunodeficiency virus
IDUs who practiced at least one unsafe injecting method were at a higher risk of HIV infection (AOR = 1.58, 95% CI: 1.09–2.28). Furthermore, the median duration of IDU behavior was 5 years in Manipur.
Knowledge and human immunodeficiency virus
HIV prevalence levels did not vary significantly (P = 0.155) between IDUs with satisfactory knowledge on HIV when compared to those who had some knowledge of HIV prevention and transmission.
Self-assessed risk to human immunodeficiency virus
Self-assessed risk of HIV was found to be a significantly associated with HIV status (χ2 = 45.86, P < 0.001). Majority of HIV infected IDUs (81.4%) who were HIV positive self-assessed themselves to have some risk of HIV infection [Table 2].{Table 2}
IDUs who had more than 10 years of IDU behavior were significantly at higher risk of infection when compared to those IDUs with <5 years of IDU behavior (OR 4.53; 95% CI: 2.99–6.86).
Discussion
IDUs living with HIV infection have been estimated to be 12.1% in Manipur. Manipur state shares a long international border with Myanmar and serves as the primary hub to illicit drug transit into India from the neighboring countries.[4] About 42% HIV-infected IDU's were in Chandel domain, 20.5% in Imphal East, 20.1% in Thoubal, and 17.4% in Senapati. Concurrently, recent HIV sentinel surveillance conducted in five districts of Manipur in the year 2017 also reported high HIV prevalence among IDUs in Thoubal (25.6%), Chandel (20.40% and 16.94% in two sites), and Senapati (14.11% and 8.03% in two sites).
Factors associated with human immunodeficiency virus infection
The factors significantly associated with HIV prevalence were occupation, age, education, injecting practices, place of injection, and the level of risk perception to HIV infection.
Older age group (39 years and above) had higher HIV prevalence (27.2%), which was in line with the study conducted in Nagaland and Manipur.[8],[9] Majority of IDUs had secondary level education and this group had more HIV prevalence (14.4%) as compared to other education subcategories. Higher the education level, lower was the odds of HIV infection risks. This association between education and HIV prevalence levels has been documented in some of the earlier studies as the Nigerian study[10] and has been contradicted in few other studies.[9] Nevertheless, the association could be due to the fact that educated IDUs are more accessible to the written materials of HIV awareness and prevention methods when compared to the illiterates, and hence, the illiterates are at a higher risk of infection. In addition, the HIV awareness is spread at schools and colleges through activities such as Red Ribbon Clubs;[11] hence, literate IDUs are more likely to be at lower risk of infection. Since the majority of the IDUs had schooling only up to standard 10, incorporating the awareness programs at secondary levels (class 6–10) in schools will be helpful in curbing the disease spread among the IDUs with secondary level education.
IDUs employed as laborers/manual workers and unemployed were at a higher risk of HIV infection than those who were employed in other services. About 11.3% of IDUs self-reported to have at least one symptom of STIs. However, a reverse association was observed between the presence of STI symptoms and HIV infection, as reported in earlier studies.[12] This could be because the number of STI symptoms included in the surveillance was limited to three and the status of the STI symptom was self-reported by the respondent. Hence, this reverse association may not be accounted for reduced risk of HIV infection among the IDUs with STIs. Similarly, a reverse association was found between safe sexual practices and HIV prevalence, and the same has been observed in many other studies. With an increase in safe sexual practices, the likelihood of HIV infection decreases;[8],[13] however, HIV prevalence was higher among IDUs with safe sexual practices than those with at least one unsafe sexual practice. This could be because of the possibility that IDUs who were practicing unsafe sex have now shifted toward safe sexual practices after becoming aware of their disease status. This could be accounted for desirable behavior changes as consistent safe sex practices among the infected IDUs will have a positive impact on the prevention of disease transmission.
IDUs injecting at their own house were more likely to be HIV positive, comparing with those who injected at drug dealers/peddlers place, contrary to the results from Chennai-based study.[14] This could be because home-based IDU practices are more common in Northeast India when compared to South India. Besides, the frequency of sharing syringes or needles in a home-based setting is higher as compared to that of a public setting which may involve strangers.[15]
IDUs with unsafe injecting practices such as sharing needles/syringe, drawing from the same container, and repeated use of needle/syringe and IDUs with longer duration of IDU practice were more likely to be HIV positive, as reported in the previous literatures.[8],[14] Knowledge on HIV prevention and transmission did not alter the HIV prevalence. Likewise, more than half of the IDUS (57.35%) self-assessed themselves to have some risk to HIV, and accordingly, the HIV prevalence was higher among those self-perceived at risk IDUs. This clearly indicates a clear gap between awareness, self-perception of risk behaviors, and safe sexual or injecting drug behavior practices.
Conclusion
The study clearly emphasizes that awareness of HIV or risk perception alone is not sufficient to halt disease transmission among the IDUs in Manipur. More emphasis on safe injecting practices would reduce the disease transmission among IDUs in Manipur.
Acknowledgments
The authors would like to thank the Project Director of Manipur State AIDS Control Society, Dr. T. Gambhir, Regional Institute of Medical Sciences, Imphal, and all the referral laboratories for their support in completing the surveillance activities in a timely manner. The authors also express their special gratitude to Dr. Sanjay Madhav Mehendale, former Additional Director General, Indian Council of Medical Research, New Delhi; Prof. DCS Reddy, Former Professor and Head, Department of PSM, Banaras Hindu University, Varanasi; Dr. Arvind Pandey, Former Director, ICMR-National Institute of Medical Statistics, New Delhi; and Prof. Shashi Kant, Professor and Head, Department of Community Medicine, AIIMS, New Delhi, for their immense contribution and technical inputs toward establishing a robust HIV surveillance system in India.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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