|Year : 2020 | Volume
| Issue : 5 | Page : 26-31
Socio-demographic factors associated with HIV prevalence among pregnant women attending antenatal clinics in six Southern States of India: Evidences from the latest round of HIV sentinel surveillance
Santhakumar Aridoss1, Nagaraj Jaganathasamy2, Arvind Kumar3, Manikandan Natesan2, Rajatashuvra Adhikary4, Elangovan Arumugam5
1 Scientist C, HIV Surveillance, Chennai, Tamil Nadu, India
2 Scientist B, HIV Surveillance, Chennai, Tamil Nadu, India
3 Associate Consultant, Strategic Information and Surveillance, National AIDS Control Organization, Ministry of Health Family Welfare, Government of India, New Delhi, India
4 National Professional Officer (HIV/AIDS), HIV Surveillance, WHO India Country Office, New Delhi, India
5 Scientist G, Computing and Information Science, ICMR-National Institute of Epidemiology, Chennai, Tamil Nadu, India
|Date of Submission||15-Oct-2019|
|Date of Decision||04-Feb-2020|
|Date of Acceptance||16-Feb-2020|
|Date of Web Publication||14-Apr-2020|
Dr. Elangovan Arumugam
ICMR-National Institute of Epidemiology, R-127, 2nd Main Road, TNHB, Ayapakkam, Chennai - 600 077, Tamil Nadu
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: HIV/AIDS is a global public health issue and its transmission in a defined geographic region is influenced by the interplay of sociodemographic and behavioral factors. Better understanding of sociodemographic characteristics of HIV-positive individuals is required to prevent the spread of HIV among the general population. Objectives: The objective of the study was to find the association between HIV prevalence and sociodemographic characteristics of pregnant women aged 15–49 years attending the antenatal clinics (ANCs) in six Southern states of India. Methods: The data from the latest round of HIV sentinel surveillance, a cross-sectional study, conducted during January–March 2017 among ANC attendees were considered for this analysis. Blood samples along with other relevant information were collected from 98,634 pregnant women from 248 sites across the states. The association between HIV prevalence and sociodemographic variables was examined using multivariable logistic regression. Results: The highest HIV prevalence was reported in Karnataka (0.38%) and Andhra Pradesh (0.38%), followed by Telangana (0.33%), Odisha (0.28%), Tamil Nadu (0.27%), and Kerala (0.05%). In all states, the prevalence was highest among illiterate pregnant women exception being Kerala, wherein the prevalence was highest in pregnant women with schooling up to primary education. A significant association was found between HIV prevalence and spouse occupation in Karnataka and Odisha and spouse migration in Andhra Pradesh and Karnataka. Conclusions: Need for improvising the interventions for the young, illiterates, having a migrant spouse, and spouse occupation as truckers/hotel staff is recommended to the stakeholders involved in HIV management of the six southern states of India.
Keywords: Antenatal clinic attendees, antenatal clinic, HIV sentinel surveillance, prevention and control, sociodemographic factors
|How to cite this article:|
Aridoss S, Jaganathasamy N, Kumar A, Natesan M, Adhikary R, Arumugam E. Socio-demographic factors associated with HIV prevalence among pregnant women attending antenatal clinics in six Southern States of India: Evidences from the latest round of HIV sentinel surveillance. Indian J Public Health 2020;64, Suppl S1:26-31
|How to cite this URL:|
Aridoss S, Jaganathasamy N, Kumar A, Natesan M, Adhikary R, Arumugam E. Socio-demographic factors associated with HIV prevalence among pregnant women attending antenatal clinics in six Southern States of India: Evidences from the latest round of HIV sentinel surveillance. Indian J Public Health [serial online] 2020 [cited 2020 May 29];64, Suppl S1:26-31. Available from: http://www.ijph.in/text.asp?2020/64/5/26/282417
| Introduction|| |
Ever since its incidence in the 1980s, HIV/AIDS continues to be a serious global public health issue. Globally, 37.9 million people are living with human immunodeficiency virus (PLHIV), with 1.7 million being newly infected as per the reports in 2018. India is the third-largest country for HIV epidemic, worldwide, after South Africa and Nigeria, with 2.1 million PLHIV. The first case of HIV infection in India was detected in 1986 among female sex workers in Chennai. During the epidemic inception, the disease was more concentrated in the South and Northeast; the four Southern states (Andhra Pradesh, Karnataka, Maharashtra, and Tamil Nadu) and two Northeastern states (Manipur and Nagaland) reported a high HIV prevalence among the pregnant women and were classified as high-prevalence states. The disease, however, eventually progressed and became widespread. The timely interventions carried out at various levels in response to the infection had a great impact in containing the spread of infection. Overall, India's HIV epidemic has declined; new infections declined by 27%, and AIDS-related deaths declined by 56% between 2010 and 2017. India is now considered as a nation with a low HIV prevalence (adult prevalence <1%). The epidemic in India is concentrated among high-risk group (HRG) populations including female sex workers, men who have sex with other men, transgender people, and injecting drug users. The infection is generally transmitted from HRGs to low-risk groups such as the general population through bridge populations such as migrants and truckers. Hence, containing the disease at the HRG level is deemed to be effective in preventing the disease spread to the general population. For this, India implements one of the world's largest and most robust HIV sentinel surveillance (HSS), a biennial system, which estimates the HIV prevalence among various HIV subpopulations: HRG, bridge population, and the general population. Pregnant women are a good representation of the sexually active population among the general population. HSS among the pregnant women, thus, serves as one of the key indicators for HIV prevalence estimation of the general population. In most countries, the HIV surveillance data are considered to be one of the best to track the epidemics pattern, as it enables analysis of the sociodemographics characteristics, associated with HIV transmission. HIV transmission is mainly driven by the sociodemographic and behavioral characteristics of an individual. Consequently, a thorough analysis of the sociodemographic characteristics of the pregnant women and its potential association with HIV infection will greatly influence HIV prevention and control measures. The objective of this study is to analyze the HSS data collected in 2017 to find any potential association between the HIV prevalence and sociodemographic characteristics of pregnant women aged 15–49 years attending the antenatal clinics (ANCs) in six Southern states of India.
| Materials and Methods|| |
Study design and area
The study involves the analysis of data collected during the 15th round of HSS conducted from January to March in 2017 among pregnant women attending designated ANCs. The states included are Andhra Pradesh, Karnataka, Kerala, Odisha, Tamil Nadu, and Telangana.
HSS essentially was a cross-sectional study that follows a consecutive sampling method, employing a linked anonymous test approach and two-test protocol.
Study population and sampling
A total of 98,634 pregnant women were recruited from 248 sites across all six states included in this study. The sample size was fixed at 400 based on the standardized operational protocols. Pregnant women aged 15–49 years attending designated ANCs for the 1st time during the surveillance period were included following a consecutive sampling method to eliminate sampling bias.
Sociodemographic characteristics of all recruited patients were recorded and blood samples were collected from all eligible respondents. Linked anonymous testing approach was followed to improve the antiretroviral therapy (ART) referral and linkage of the HIV-positive pregnant women, and two-test procedure was used to confirm the HIV status of the samples. Standard operating procedures were followed for collecting and testing the samples across all the sites, as mentioned elsewhere.
Descriptive statistics were used to describe the characteristics of the study participants. In all states, the association between HIV prevalence (outcome variable) and sociodemographic variables (explanatory variables) was examined using multivariable logistic regression. Odds ratios and P values were used to indicate the significance of the influence of the explanatory variable on the outcome and the extent of that influence. All associated sociodemographic factors (age, literacy status, residence, occupation, and spouse migration status) that were at the significant level with P < 0.20 on unadjusted logistic regression were further examined in multivariable logistic regression. Following the selection of significant variables, the suitability of the model fit was assessed with the Hosmer–Lemeshow test with the significance level of 5%. Data were analyzed using SPSS software IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0. Armonk, NY: IBM Corp. P 0.05 was used to indicate statistical significance.
Ethical approval was exempted as this was a surveillance activity where the HIV test was anonymous and the results were not used for determining the HIV status of a person. However, the purpose of the study was informed to the participants before the sample collections. The same is endorsed in Item No. 6 under Chapter III of the India HIV act 2017.
| Results|| |
Socio-demographic profile of the study subjects
Age distribution varied between the states (P < 0.001); the distribution of respondents of age ≤24 years ranged from 38.7% in Kerala to 74.1% in Andhra Pradesh. Based on the education, the proportion of illiterate pregnant women was highest in Telangana (17.2%) and lowest in Kerala (0.6%), whereas the proportion of pregnant women with higher secondary and tertiary level of education ranged from 17.1% in Odisha to 67.1% Kerala. Most of the participants were residents of rural areas (≥60%) except in Telangana, a recently formulated state in India. In all states, more than 65% of the respondents were housewives, the highest proportion being in Tamil Nadu and Odisha (≥90%) (data not shown). The spouse migration wherein the spouse had stayed away from the family for more than 6 months was as high as 11.1% (Kerala) to 1.1% (Karnataka and Telangana). The proportion of pregnant women who had never been tested for HIV ranged between 85.3% (Tamil Nadu) and 32.9% (Odisha).
HIV prevalence by socio-demographic characteristics
Among the six South Indian states included in this study, the highest HIV prevalence among the pregnant women aged 15–49 years was reported in Karnataka (0.38%) and Andhra Pradesh (0.38%), followed by Telangana (0.33%), Odisha (0.28%), Tamil Nadu (0.27%), and Kerala (0.05%). The potential risk factors associated with HIV prevalence in each state are represented in [Table 1], [Table 2], [Table 3]. In general, younger age is considered to be associated with increased infection risk, owing to their vulnerability. However, in Karnataka, the HIV risk was significantly higher in pregnant women aged 35–49 years compared to those aged 15–24 years.
|Table 1: Factors associated with HIV prevalence among antenatal clinic attendees (Andhra Pradesh and Telangana)|
Click here to view
|Table 2: Factors associated with HIV prevalence among antenatal clinic attendees (Kerala and Tamil Nadu)|
Click here to view
|Table 3: Factors associated with HIV prevalence among antenatal clinic attendees (Karnataka and Odisha)|
Click here to view
Literacy status had a significant (P < 0.05) association with the odds of having positivity of HIV status in both unadjusted and adjusted models across the three states (Andhra Pradesh, Telangana, and Odisha). HIV prevalence was predominantly higher among the illiterates as compared to other literacy groups. Secondary and above secondary level education had significantly lower odds of infection risks in Kerala, Tamil Nadu, Andhra Pradesh, and Telangana. Education level did not significantly influence the HIV prevalence in Karnataka and Odisha. Primigravida mothers were predominantly at a higher risk of infection, except Kerala. However, the high HIV prevalence was associated with fourth- or higher-order pregnancies in all states, except Andhra Pradesh. The duration of pregnancy and residence were not significantly associated with infection risks, the exception being Telangana.
The HIV prevalence was predominantly higher among pregnant women whose spouse occupation was hotel staff/truckers in all states except Kerala. A significant association between HIV prevalence and spouse occupation was observed in two states: Karnataka and Odisha, in both unadjusted and adjusted models. The odds of infection risk in pregnant women whose spouses were truckers/hotel staff were 2 times higher than that of the laborers. While the HIV prevalence was higher among pregnant women with a migrant spouse in all states except Tamil Nadu, this association was significant in Andhra Pradesh and Karnataka. Compared to their counterparts, women with migrant spouses were at least twice at higher odds of infection risk in Andhra Pradesh (adjusted odds ratio [AOR]: 3.37, confidence interval [CI]: 1.21–9.41, P < 0.05) and Karnataka (AOR: 2.59, CI: 0.81–8.31, P < 0.05). Interestingly, the odds of HIV prevalence were significantly higher among those pregnant women in Tamil Nadu, Karnataka, and Odisha, who had previously tested for HIV, compared to those who had never been tested for HIV.
| Discussion|| |
Indian states are diverse in terms of culture, religion, race, language, and so on. Similarly, HIV in India is also heterogeneous in nature, implying that one intervention fits all may not work for the effective HIV management. Decentralized targeted intervention specific to location and sociodemographics of the population is required, for which analysis of sociodemographic characteristics for its potential association with infection risk is essential. The results indicate that a low level of education is predominantly associated with higher odds of infection risks. Although education may not be directly associated with the risk of HIV infection, education paves a way for better awareness of the disease, which eventually reflects on HIV prevention and management. Education, on the other hand, also empowers the women to be economically independent, which may relieve them from sexual exploitation, eventually resulting in reduced HIV burden. In India, comprehensive knowledge of HIV/AIDS was only found among 21.6% of young women aged 15–24 years, emphasizing the need for educating the young on HIV/AIDS prevention and control measures. State and district level interventions to create awareness through folk tales and media advertisements in local languages have been substantially successful in creating among the illiterates and those with limited access to written or printed information. These efforts are still required to promote HIV management and ART and to evade the prevailing misconceptions and stigma about HIV, for progressive disease management. Educating men, especially the young, on HIV prevention and management will have profound effects on reducing the disease burden among married women.
HIV prevalence was predominantly higher among pregnant women whose spouses were truckers, transport workers, and hotel staff, specifically in Karnataka, given its dynamic population. Dynamicity in population is often associated with the spread of infection; often, men traveling between urban and rural regions contribute to the increase in HIV prevalence. Consequently, spouses of migrants were also at substantial risk of infection, as evidenced by earlier reports.,, Even with specific targeted interventions for truckers and migrants, follow-up is a concern with these mobile populations. Again, while long-distant truckers have been covered through Targeted Interventions, little is known about the interventions for local transport workers. More targeted interventions for such a mobile population with digital-based technologies for effective follow-up services may be helpful. India has mandated HIV testing for all pregnant women to reduce the vertical transmission of the disease to the children. Early diagnosis and timely ART administration reduce the vertical transmission risk by 25 times. Hence, it is advised that all pregnant women avail ANC services in the first trimester of their pregnancy. Women of fourth- or higher-order pregnancies had predominantly higher HIV prevalence, although minimal in numbers needs attention for preventing further transmission.
As HSS is a cross-sectional survey that is conducted biennially at the same designated sentinel sites, some degree of overlap in sample selection may persist. The current analysis does not account for clustering effects due to geography and time. Migration and double counting are some of the major problems for any survey, which are not addressed.
| Conclusions|| |
Need for improvising the interventions for the young, illiterates, having a migrant spouse, and spouse occupation as truckers/hotel staff is recommended to the stakeholders involved in HIV management of the six Southern states of India.
The authors wish to thank the project directors of six state AIDS control societies for their support in completing the surveillance activities in a timely manner. The authors also express their gratitude to the concerned referral laboratories, state surveillance team members, and sentinel site personnel. Our special thanks 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
The corresponding author received funding from the National AIDS Control Organization for conducting the HSS for those six states. Permission also received for authorship and publication of this article.
Conflicts of interest
There are no conflicts of interest.
| References|| |
Simoes EA, Babu PG, John TJ, Nirmala S, Solomon S, Lakshminarayana CS, et al
. Evidence for HTLV-III infection in prostitutes in Tamil Nadu (India). Indian J Med Res 1987;85:335-8.
Paranjape RS, Challacombe SJ. HIV/AIDS in India: An overview of the Indian epidemic. Oral Dis 2016;22 Suppl 1:10-4.
Walker N, Garcia-Calleja JM, Heaton L, Asamoah-Odei E, Poumerol G, Lazzari S, et al
. Epidemiological analysis of the quality of HIV sero-surveillance in the world: How well do we track the epidemic? AIDS 2001;15:1545-54.
Ghosh P, Arah OA, Talukdar A, Sur D, Babu GR, Sengupta P, et al
. Factors associated with HIV infection among Indian women. Int J STD AIDS 2011;22:140-5.
Solomon S, Kumarasamy N, Ganesh AK, Amalraj RE. Prevalence and risk factors of HIV-1 and HIV-2 infection in urban and rural areas in Tamil Nadu, India. Int J STD AIDS 1998;9:98-103.
Halli SS, Blanchard J, Satihal DG, Moses S. Migration and HIV transmission in rural South India: An ethnographic study. Cult Health Sex 2007;9:85-94.
Gupta K, Singh SK. Social Networking, Knowledge of HIV/AIDS and Risk-taking behaviour among Migrant Workers. Bangkok: Paper Presented in the Regional Conference of IUSSP; 2002.
Saggurti N, Mahapatra B, Sabarwal S, Ghosh S, Johri A. Male out-migration: A factor for the spread of HIV infection among married men and women in rural India. PLoS One 2012;7:e43222.
Robinson JL. Canadian Paediatric Society (CPS), Infectious Diseases and Immunization Committee, Testing for HIV infection in pregnancy, Paediatrics & Child Health 2008;13:221-4. Doi: doi.org/10.1093/pch/13.3.221.
[Table 1], [Table 2], [Table 3]