|Year : 2013 | Volume
| Issue : 2 | Page : 58-65
Sexual behavior and job stress in software professionals, Bengaluru - India
Giridhara R Babu1, Tanmay Mahapatra2, Sanchita Mahapatra2, Roger Detels2
1 Department of Epidemiology, Public Health Foundation of India, IIPH H, Bangalore Campus, Bengaluru, Karnataka, India
2 Department of Epidemiology, University of California, Los Angeles, California, USA
|Date of Web Publication||17-Dec-2013|
Giridhara R Babu
Public Health Foundation of India, IIPH H, Bangalore Campus, SIHFW Premises, Beside Leprosy Hospital, 1st Cross Magadi Road, Bengaluru - 560 023, Karnataka
Source of Support: The study was supported through NIH/Fogarty
International center, Fogarty/UCLA AIDS International Research &
Training Program. (Grant Number: D43 TW000013) and Public Health
Foundation of India provided partial grant, Conflict of Interest: None
Background: Sexually transmitted diseases are now gradually affecting the general population groups increasingly. Our earlier observations from qualitative research called for an effort to understand the sexual exposure, activity and behavior of the workers in these software professionals in Bengaluru, India. Aim: The current study is explored to understand the association of the sexual behaviors with Job. Materials and Methods: The study design employed was a cross-sectional study using a mixed sampling method. A total of 1071 subjects from software sector in Bengaluru, the capital city of Karnataka completed the self-administered questionnaire. The source population comprised all information technology/information technology enabled services (IT/ITES) professionals aged 20-59 years working in "technical functions" in 21 selected worksites (units) of the software industry. The exposure of interest was job stressors and the outcome measures were sexual behaviors in the form of having multiple sexual partners, paid sex in last 3 months and frequency of intercourse with irregular sexual partners and condom use with regular partners during last sexual act. Results: Among the study population, 74.3% reported not using a condom during their last vaginal intercourse with their regular partner. Regression estimates indicated that workers with high physical stressors had 6 times odds of having paid for sex in last 3 months and those with a moderate level of income related stress had 2.4 times likelihood of not using a condom during the last sexual intercourse with their regular partner. Conclusion: There is scope for starting prevention programs among young professionals in the IT/ITES sector to mitigate their possible risk behaviors.
Keywords: Job stress, sexual behaviour, software professionals
|How to cite this article:|
Babu GR, Mahapatra T, Mahapatra S, Detels R. Sexual behavior and job stress in software professionals, Bengaluru - India. Indian J Occup Environ Med 2013;17:58-65
|How to cite this URL:|
Babu GR, Mahapatra T, Mahapatra S, Detels R. Sexual behavior and job stress in software professionals, Bengaluru - India. Indian J Occup Environ Med [serial online] 2013 [cited 2021 May 15];17:58-65. Available from: https://www.ijoem.com/text.asp?2013/17/2/58/123165
| Introduction|| |
Targeted intervention programs to prevent the spread of sexually transmitted infections (STIs) including human immunodeficiency virus (HIV) among high-risk groups like female sex workers have been scaled up considerably over the past few years in India. Although commercial sex workers and health care workers are considered to be at higher risk of acquisition of HIV, the risks for other occupational groups remain understudied. As job related aspects affecting the risk of HIV and other STIs may well vary across different occupations, workers in different jobs may well get affected by HIV and other STIs heterogeneously and the estimation of the risk of these infections among these groups requires detailed study of their sexual exposure, activity and behavioral patterns.
According to the "contact hypothesis" the social-sexual behavior of the workers at the worksite depends a lot on their scopes of contact and intermixing with the other gender at the workspace,  which can definitely vary across different occupation thus the sexual behavior of the workers are also pretty likely to vary across occupations and each occupation may have a pattern of the sexual behavior of its own. Different socio-economic and educational factors associated with different jobs may also modify these patterns.  Jobs with different income structure, autonomy, mobility may also influence the sexual behavioral patterns of the workers.  In India, evidence suggests that jobs with high mobility are likely to be associated with high risk sexual behavior. Long distance truck drivers and their assistants, apart from being at higher risk, are also found to have important roles in the transmission of STIs.  Results of a study involving workers of various private sectors in Karnataka did show that workers engaged in mining, garment/textile, sugar, construction/infrastructure and fishing industries had a higher risk of acquisition of HIV and other STIs.  A study on the sexual behavior of garment/textile workers in the southern Indian state of Tamil Nadu had documented an occupational pattern in their risky sexual behavior 4] In a study conducted among 995 men workers, aged 15-24 years from a knit city in south India, the results indicated that higher income and having more girl friends were associated with a greater likelihood for engaging in risky sexual behaviors.  In a study involving 3008 men recruited from 11 cities across Indonesia in 2009, the potential for HIV/acquired immunodeficiency syndrome transmission was found to vary across occupational groups.  Type of work, workplace environment and experiences were also found to have implications in the sexual behaviors of the employees. , Information technology (IT) sector like many other job sectors in India were also found to have a generally traditional and stereotypical gendered norms represented explicitly and implicitly, which may well entail typical patterns of sexual behaviours among the workers. 
The current study was designed to study the occupational groups of workers in the IT and information technology enabled services (ITES) sectors in Bangalore, the capital city of Karnataka state of India. Our qualitative research described elsewhere  indicated that the socio-demographic, economic and behavioral determinants of health in these workforces are somewhat different from other occupational groups. Keeping in mind the fact that the HIV and STI epidemic of India are now gradually affecting the general population groups more and more, , observations from our qualitative research called for an effort to understand the sexual exposure, activity and behavior of the workers in these two sectors. Proper understanding of these aspects thus can be considered as an initial step for designing future intervention efforts. In this context, the current study offers a model for understanding the distribution of the sexual exposure, activity and behavioral patterns among IT/ITES professionals of Bangalore. We also aim to assess the strength and direction of association (if any) between job related stress factors and high risk sexual behaviors in this population.
| Materials and Methods|| |
We conducted a cross sectional study of IT/ITES professionals in Bangalore, the 27 th largest city in the world, 3 rd largest in India by population and the IT capital of India. In 2010, Bangalore had more than 1000 IT/ITES companies and more than 150,000 IT/ITES professionals. ,,
Bangalore Metropolitan area was used as the study area which was divided into 17 geographical clusters based on clustering of IT/ITES companies. ,, The list of IT/ITES worksites in the study area stratified by the geographical clusters were used as the sampling frame. The sampling was done such that at least one worksite representing every geographical area having IT/ITES companies in Bangalore gets selected.  Thus from 17 selected geographic clusters, 21 worksites who agreed to participate were selected. In each site, after obtaining necessary administrative permissions, eligible willing employees were recruited after providing informed consent until the desired sample size was reached.
IT/ITES professionals aged 20-59 years working for at least 1 year in "technical functions" in the selected worksites (units) of the IT/ITES sector and who provided informed consent for participation were eligible for recruitment. "Technical functions" referred to all job categories involved in human-computer interface within these companies selected for the study as per the list approved by according to Revised Indian National Classification of Occupations 2004. 
A qualitative study was conducted initially  to explore the health related behaviors of the IT/ITES workers in Bangalore. Having multiple sexual partners, frequent intercourse with casual partners and having paid for sex during last 3 months were considered as indicators for sexual risk behaviors in this study. It was found that 12.31% of the participants reported at least one of them. Thus assuming the proportion of persons having risky sexual behavior (p) being 0.1231 with the desired precision (assumed on the basis of small expected baseline levels) of 0.02 (d) at a significance level of 0.05 (α) the required sample size was calculated to be 1037. , To compensate for an assumed 20% non-response rate, 1296 subjects were supposed to be invited. 1305 IT/ITES workers were invited by the respective human resource department of the selected worksites, among which 171 didn't return the questionnaire, 51 were found ineligible later as they were in the work for <1 year and 12 persons returned blank forms. Thus, 1071 (77% of all invited) subjects were included in the study. Among them, 509 subjects were from the IT sector and 472 subjects from ITES sector.
Using the anonymous questionnaire, we collected information on gender, ever use of tobacco, regular physical exercise and habit of drinking alcohol. Marital status (married/single), age at sexual debut and whether married more than once or not were enquired to have an idea about the sexual exposure of the participants. Information on who usually initiated sex among the partners (participant/partner), quality of sexual life (as rated by the participant as poor/good/excellent), having sexual intercourse in last 1 month (yes/no) and its frequency with a regular partner (none/occasionally/sometimes/often) in last 1 month were collected to have an idea about the sexual activity of the participants. Sexual risk behaviors were assessed based on the dependent variables: Having multiple partners (determined by the response to the question: "Currently, do you have multiple partners for sex?", with the response being yes/no), paid for sex in last 3 months (determined by the response to the question: "In last 3 months, did you pay to have sexual intercourse with another person [male of female]?", with the response being yes/no) and frequency of vaginal intercourse with a casual partner (other than wife/husband/regular partner whom the participants didn't pay to have sex) in last 3 months (response being coded as: 0 = none, 1-6 = occasional, 7-21 = sometimes and >21 = often) in last 3 months and condom use (determined by the response to the question: "Did you use a condom during your last vaginal intercourse with wife/partner/husband" and the response being coded as: yes/no).
Job stressors are defined as "working conditions that may lead to acute reactions, or strains in the worker."  Overall occupational stress was measured using occupational stress index (OSI) Questionnaire (which is not copyright protected and flexible for modification) with permission from Belkic and Savic  Belkic ,, Information on job stressors, buffer factors, non-work activities and acute physiologic responses were collected as per the suggestion of the theoretical model described in the development of OSI. ,,, Using the questionnaire, job stress levels (low/moderate/high) were also measured in individual contextual stress domains  details of which are measured in [Table 1].
The study was reviewed and approved by the UCLA Institutional Review Board (IRB, #G09-12-002-01, IRB#10-001348) and the ethics committee of The Public Health Foundation of India (TRC-IEC 40/10).
The collected data were entered in MS excel and cleaned. The data from the cross sectional survey was analyzed using SAS 9.1.3 (SAS software, Version 9.3 of the SAS System for Windows. Copyright © (2012) SAS Institute Inc. SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc., Cary, NC, USA.).  Among 1071 eligible subjects, the percentage of completeness on sensitive questions varied. The completeness for some of the questions was good such as the questions related to marital status (99.8% answered it), paid for sex (90%), married more than once (85.7%), multiple sex partner (85.3%), frequency of intercourse in the last 3 months with a casual partner (82.5%) and frequency of intercourse in the last month (77.6%). At first we did a descriptive analysis to assess the patterns of the distributions of sexual exposure, activity and behaviors of the participants. Next, we conducted logistic regression analyses for estimating associations of each of the occupational stress factors with sexual risk behaviors, controlling for gender, marital status, ever use of tobacco, regular physical exercise and habit of drinking alcohol as from prior information based on literature review these factors had the potential to confound the association between job stress and sexual behaviors. ,,,,,,,,,,,,,,,,,,,,, While performing regressions using models for frequency of vaginal intercourse with a casual partner in last 3 months, cumulative logistic regression was used for efficient analyses as this outcome variable had more than 2 categories.
| Results|| |
Information regarding 1071 voluntary participants was included in our analysis. The number of responses varied across interview questions and different questions were not applicable to different participants. Hence in both our descriptive and associational analyses numbers of included observations did vary for different variables of interest.
The average age of the participants was 28.5 years and it was almost same among males and females (28.6 and 28.3 years respectively). Mean age for sexual debut was 27 years (27.1 years among males and 26.7 years among females); mean age of marriage was 27.7 years (28 years among males and 26.9 years among females) and mean age at having first paid sex was 25.1 years and it was somewhat higher among females (24.9 years among males and 27.8 years among females) [Table 2].
|Table 2: Distribution of the socio-behavioural characteristics of participating IT/ITES professionals of Bangalore|
Click here to view
Majority of the participants (58.5%) had 2.1-7 years and very few had more than 12 years of work experience in IT/ITES sector. The picture was almost same in both genders. Higher proportion of participating workers (67%) hadn't ever used tobacco or drank alcohol although male workers smoked and drank more than females. Majority of the workers (62.6%) in both genders (61.7% male and 64.3% females) didn't exercise regularly [Table 2].
Among the responding participants, sexual acts were usually initiated by both male and female partners together as reported by both genders (73.7% males and 74.5% females reported so). Quality of sexual life was rated as good by the majority in both sexes (46.6% males and 59.1% females rated so) although proportion was higher among females. Larger proportion of the responders (62.5%) was not sexually active and the scenario was comparable across the gender strata [Table 2].
Among 914 subjects who answered the question, only 6.4% of males and 3.6% of females reported having multiple sexual partners. Among responders (884), 79.7% of males and 69.4% of females reported not having intercourse with casual partners in the last 3 months, whereas 6% of males and 13% females reported often having intercourse with casual partners in last 3 months. Among 964 responders, only 5% males and 2% females reported having paid for sex in the last 3 months [Table 2].
The adjusted estimates for association between job stress and sexual risk behaviors indicate that compared to those with low level of stress in respective contextual stress domains, participants with a moderate level of stress related to length of experience were 70% less likely and high level of shift related stress were 60% less likely to have a higher frequency of sexual intercourse with their casual partner in last 3 months. Subjects with a high level of shift work related stress, compared with their counterparts with low level of stress had 60% lower odds of using a condom during their last sexual act with a regular partner. Moderate level of income related stress compared to the corresponding low level was found to be associated with 2.4 times likelihood of using a condom during the last sexual intercourse with their wife/husband/regular partner. Workers who had a high level of physical stressors compared to those with lower levels had 6 times odds of having paid for sex in last 3 months [Table 3].
|Table 3: Adjusted estimates*for the association between occupational stress factors and sexual behaviours among participating IT/ ITES professionals of Bangalore|
Click here to view
| Discussion|| |
Evidence regarding sexual behavior studied across occupational groups and designing intervention programs based on the same is relatively scarce and is limited to only HIV prevention in a few geographical areas.  It is reported that high-risk sexual behavior among males is an influential factor for the increased risk of HIV transmission in India.  Furthermore, high risk sexual behaviors leading to increased risk of acquisition of STIs including HIV mainly affect sexually active young people.  Most of the earlier studies done among IT/ITES professionals explored only physical health such as musculoskeletal symptoms, sleeping disorders, ear problems and digestive and eye diseases.  To the best of our knowledge, this is the first study to examine stress and sexual behavior in IT and ITES professionals in India.
Higher proportion of the participants were married, had normal age of sexual debut, reported initiation of sex being a joint decision, having good sexual life, less sexually active. Distributions were similar for male and female participants.
In our study population, we found that participants with a moderate level of stress related to length of experience and high level of shift related stress were less likely to have a higher frequency of sexual intercourse with their casual partner in last 3 months compared with those with low level of corresponding stressors. Workers who had a high level of physical stressors compared with their low-stressed counterparts, had a higher likelihood of having paid for sex in the recent past. With reference to lower stress, persons with a moderate level of income stress had a higher likelihood of using a condom during the last sexual intercourse with their wife/husband/regular partner. Our study also reported an inverse association between duration of experience stressors and shift work with sexual intercourse with their casual partner in the last 3 months. We also found that income stressors had higher and shift work had lower odds of using a condom during last sexual intercourse. There is scarce evidence available on stressors as determinants of sexual behavior, specifically under occupational settings. 
Although it seemed from the adjusted point estimates that other occupational stressors were also associated with high risk sexual behaviors, the result from this study exploring these associations suffered from lack of power. The adjusted estimates for the association between high income related stress and having multiple partner and paid sex, high physical stress, having multiple partners, high work environment related stress and having frequent sex with casual partners all corroborated with positive associations compared to their lower stressed counterparts although results were imprecise. The likely reason is the lower number of responses. Although the information was largely complete (with completeness rate more than 80%), less number of participants acknowledged or proceeded with further questions exploring high-risk behavior. Hence, despite being assured of confidentiality and understanding the anonymous nature of the study, the participants might be reluctant to divulge any information which they may view as very sensitive and they aren't comfortable answering this.
Our study had some limitations. There might be several reasons why the response rates for answering individual sensitive questions of the sexual behavior questionnaire were poor. The response rates for sexual behavior questionnaire varied across different questions, with few questions answered by all the participants while only few people answered some sensitive questions. In Karnataka state, Bradley et al. reported that young people rarely discuss about healthy sexuality and safe sex practices.  One of the predominant reasons for this is stigma about discussing sex and sexuality issues among young people. Another possible reason may be the misconception that engaging in high-risk sexual activity is notional of masculinity amongst some subsets of youth. Our study did not have adequate power to detect and report some of the determinants contributing to high-risk behaviors. Furthermore, comprehensive stress assessment was beyond the scope of this study. As it is cross-sectional study, temporal ambiguity is another limitation. Regarding representativeness, although we are very confident about having somewhat good representativeness based on our sampling design, still we caution our readers that the results of the study should be extrapolated beyond the study sample carefully.
| Conclusions and Future Directions|| |
Our study explored the distribution and determinants of sexual behavior in a highly economically productive occupational setting. Findings of our study can be useful toward designing larger studies that may help in the planning of intervention programs specifically focused in this workplace. The relation of stress and sexual behavior is not unexpected and this study provides two positive associations toward this. Physical environment stressors were associated with paid sex in the recent past. Income stress had higher likelihood of not using condom during the last sexual intercourse with their wife/husband/regular partner. We also found that workers with moderate stress regarding work experience and higher shift work related stress were less likely to have sexual risk behaviors. These findings calls in for closer examination of these factors in larger sample and further plan suitable interventions to address contextual stressors.
It seems necessary to design intervention programs targeting worksites to increase awareness regarding sexual risk behaviors among these workers. Such interventions would yield greater results if providing information and awareness targeted to single, divorced and widowed younger persons. It is important to concentrate on the subgroup with multiple partners, who might also share other risk behaviors who can be potential transmitters of STI's.
In conclusion, there is scope for improving awareness in promoting safe sex practices such as condom use and knowledge about alleviating high-risk behaviors in IT/ITES professionals and addressing occupational stress factors may be included in the scope of these programs.
| Acknowledgments|| |
I thank Shanth Kumar for dedicated support in the field activity and data management. I also thank T S Ramesh and Srinivas Prasad for administrative support.
| References|| |
|1.||Gutek BA, Cohen AG, Konrad AM. Predicting social-sexual behavior at work: A contact hypothesis. Acad Manage J 1990;33:560-77. |
|2.||Rosen S, Simon JL. Shifting the Burden of HIV/AIDS. "Shifting the Burden of HIV/AIDS." (2010). Health and Development Discussion Paper No. 1 May 2002. Center for International Health Boston University School of Public Health. web: http://open.bu.edu/xmlui/bitstream/handle/2144/1296/cih_hddp_1.pdf?sequence=1. |
|3.||Pandey A, Benara SK, Roy N, Sahu D, Thomas M, Joshi DK, et al. Risk behaviour, sexually transmitted infections and HIV among long-distance truck drivers: A cross-sectional survey along national highways in India. AIDS 2008;22 Suppl 5:S81-90. |
|4.||Halli SS, Buzdugan R, Ramesh BM, Gurnani V, Sharma V, Moses S, et al. Assessing HIV risk in workplaces for prioritizing HIV preventive interventions in Karnataka State, India. Sex Transm Dis 2009;36:556-63. |
|5.||Audinarayana N. Sexual behaviour and its determinants among young never-married male factory workers in a South Indian Knit City. J Popul Soc Stud 2009;18:155-74. |
|6.||Mustikawati DE, Morineau G, Nurhayati, Irmaningrum Y, Riono P, Priohutomo S, et al. Sexual risk taking, sexually transmitted infections and HIV prevalence among four "high-risk" occupational groups of Indonesian men. Sex Transm Infect 2009;85:391-6. |
|7.||D′Mello M. Gendered selves and identities of information technology professionals in global software organizations in India. Inf Technol Dev 2006;12:131-58. |
|8.||Babu GR, Roger Detels. A Qualitative study about work-environment of software professional in Bengaluru, India [Papers]. Ch. 3. In Prevalence of Job Stress, General Health Profile and Hypertension among Professionals in the Information Technology Sector in Bengaluru, India. University of California Los Angeles; 2012. Retrieved from: http://escholarship.org/uc/item/3137m5hh:" |
|9.||Sarkar K, Bal B, Mukherjee R, Niyogi SK, Saha MK, Bhattacharya SK. Epidemiology of HIV infection among brothel-based sex workers in Kolkata, India. J Health Popul Nutr 2005;23:231-5. |
|10.||Das D, Gupta R. Meta analytic measurement of HIV/AIDS awareness, prevention and accepting attitude toward people living with HIV/AIDS in the seven states of North East India. Health 2011;3:868-78. |
|11.||Babu GR, Roger Detels. Methods of IT/ITES study in Bengaluru, India [Papers]. Ch. 2. In Prevalence of Job Stress, General Health Profile and Hypertension among Professionals in the Information Technology Sector in Bengaluru, India. University of California Los Angeles; 2012. Retrieved from: http://escholarship.org/uc/item/3137m5hh. |
|12.||The Bruhat Bengaluru Mahanagara Palike. Zonal map of Bangalore . Downloaded from web. 20 th May 2012. http://bbmp.gov.in/maps. |
|13.||The Bruhat Bengaluru Mahanagara Palike. Zonal map of Bangalore . Downloaded from web. 20 th May 2012. http://bbmp.gov.in/home. |
|14.||Altman DG. Statistics in medical journals: Developments in the 1980s. Stat Med 1991;10:1897-913. |
|15.||McCullagh P. Regression models for ordinal data. J R Stat Soc Series B Stat Methodol 1980;2:109-42. |
|16.||Teddlie C, Yu F. Mixed methods sampling. J Mix Methods Res 2007;1:77-100. |
|17.||National Association of Software and Service Companies. The IT-BPO Sector in India: Strategic Review 2012. NASSCOM ®, New Delhi 2012. |
|18.||Government of India, Ministry of Communications, Depatment of Information Technology. Annual Report, Information Technology, 2007- 08 Ministry of, downloaded from http://deity.gov.in/sites/upload_files/dit/files/annualreport2007-08.pdf. |
|19.||Dean A, Sullivan K, Soe M. OpenEpi: Open source epidemiologic statistics for public health, version 2.3. Update 2009;20: Downloaded from web http://www.openepi.com/OE2.3/Menu/OpenEpiMenu.htm. |
|20.||Daniel WW. Biostatistics: Basic Concepts and Methodology for the Health Sciences. John Wiley and Sons; 2010. |
|21.||Belkic K, Savic C. The occupational stress index - An approach derived from cognitive ergonomics applicable to clinical practice. Scand J Work Environ Health 2008;34:169. |
|22.||Belkic K. The Occupational Stress Index: An Approach Derived from Cognitive Ergonomics and Brain Research for Clinical Practice. Cambridge: Cambridge International Science Pub, 2003. Print. |
|23.||Belkic K. Occupational stress index: An introduction. Scand J Work Environ Health 2000;1:73-86. Web: http://www.workhealth.org. |
|24.||Belki K. Occupation-specific versus general self-report measures to assess psychosocial workplace exposures-dilemmas and potential solutions to bridge the gap. Work and Health; 2001. p. 258-60. No. 10. |
|25.||Institute S. SAS Institute Inc., Cary, NC, USA. Version 9.3. SAS Institute Cary, NC. 2002. |
|26.||Abraham L, Kumar KA. Sexual experiences and their correlates among college students in Mumbai City, India. Int Fam Plann Persp 1999;25:139-52. |
|27.||Alexander M, Garda L, Kanade S, Jejeebhoy S, Ganatra B. Correlates of premarital relationships among unmarried youth in Pune district, Maharashtra, India. Int Fam Plan Perspect 2007;33:150-9. |
|28.||Nicoll A, Stephenson J, Griffioen A, Cliffe S, Rogers P, Boisson E. The relationship of HIV prevalence in pregnant women to that in women of reproductive age: A validated method for adjustment. AIDS 1998;12:1861-7. |
|29.||Arora P, Nagelkerke N, Sgaier SK, Kumar R, Dhingra N, Jha P. HIV, HSV-2 and syphilis among married couples in India: Patterns of discordance and concordance. Sex Transm Infect 2011;87:516-20. |
|30.||Basu I, Jana S, Rotheram-Borus MJ, Swendeman D, Lee SJ, Newman P, et al. HIV prevention among sex workers in India. J Acquir Immune Defic Syndr 2004;36:845-52. |
|31.||Bedimo AL, Bennett M, Kissinger P, Clark RA. Understanding barriers to condom usage among HIV-infected African American women. J Assoc Nurses AIDS Care 1998;9:48-58. |
|32.||Bowen KJ, Dzuvichu B, Rungsung R, Devine AE, Hocking J, Kermode M. Life circumstances of women entering sex work in Nagaland, India. Asia Pac J Public Health 2011;23:843-51. |
|33.||Campbell C. Migrancy, masculine identities and AIDS: The psychosocial context of HIV transmission on the South African gold mines. Soc Sci Med 1997;45:273-81. |
|34.||Campbell C, Williams B. Beyond the biomedical and behavioural: Towards an integrated approach to HIV prevention in the southern African mining industry. Soc Sci Med 1999;48:1625-39. |
|35.||Dandona R, Dandona L, Gutierrez JP, Kumar AG, McPherson S, Samuels F, et al. High risk of HIV in non-brothel based female sex workers in India. BMC Public Health 2005;5:87. |
|36.||Dandona R, Dandona L, Kumar GA, Gutierrez JP, McPherson S, Samuels F, et al. Demography and sex work characteristics of female sex workers in India. BMC Int Health Hum Rights 2006;6:5. |
|37.||Taraphdar P, Dasgupta A, Saha B. Coital debut of people living with HIV/AIDS attending school of tropical medicine, Kolkata. Indian J Public Health 2009;53:240-2. |
|38.||Dolan K, Larney S. HIV in Indian prisons: Risk behaviour, prevalence, prevention and treatment. Indian J Med Res 2010;132:696-700. |
|39.||Egger M, Pauw J, Lopatatzidis A, Medrano D, Paccaud F, Smith GD. Promotion of condom use in a high-risk setting in Nicaragua: A randomised controlled trial. Lancet 2000;355:2101-5. |
|40.||Heywood M. Mining industry enters a new era of AIDS prevention. Eye witness: South Africa. AIDS Anal Afr 1996;6:16. |
|41.||Kenen RH, Armstrong K. The why, when and whether of condom use among female and male drug users. J Community Health 1992;17:303-17. |
|42.||Kesavachandran C, Rastogi SK, Das M, Khan AM. Working conditions and health among employees at information technology - Enabled services: A review of current evidence. Indian J Med Sci 2006;60:300-7. |
|43.||Shah P, Reddy P, Hegde S. Stress: Occupational health disorder amongst computer professionals. Indian J Occup Health 1999;3:71-3. |
|44.||George G, Sprague C. HIV prevention in the world of work in sub-Saharan Africa: Research and practice. Afr J AIDS Res 2011;10 Suppl 1:291-300. |
|45.||McManus A, Dhar L. Study of knowledge, perception and attitude of adolescent girls towards STIs/HIV, safer sex and sex education: (A cross sectional survey of urban adolescent school girls in South Delhi, India). BMC Womens Health 2008;8:12. |
|46.||Erausquin JT, Reed E, Blankenship KM. Police-related experiences and HIV risk among female sex workers in Andhra Pradesh, India. J Infect Dis 2011;204 Suppl 5:S1223-8. |
|47.||Bradley J, Rajaram S, Moses S, Bhattacharjee P, Lobo AM, Ramesh BM, et al. Changes in HIV knowledge, and socio-cultural and sexual attitudes in South India from 2003-2009. BMC Public Health 2011;11 Suppl 6:S12. |
[Table 1], [Table 2], [Table 3]