The prevalence of HIV in high risk
population is influenced significantly the behavioral and sociodemographic
characteristics. However, considering the complexity of behavior among female
sex workers, the relationship between a particular behavioral pattern and the
HIV status of this “at risk” population assumes significance. Data generated in
a community-based cross-sectional study earlier carried out to assess the
prevalence estimates, at district level, of HIV status in eight districts of
State of Andhra Pradesh, India was used to carry out factor analysis to explore
the role of demographic and behavioral pattern and their relationship with the
HIV status among female sex workers. Data on 3083 female sex workers in the
study revealed that there existed nine patterns among demographic and
behavioral characteristics, which explained 62% of the total variation through
factor analysis. Further, cluster analysis was performed to identify the groups
of individuals having similar characteristics. Two of those clusters had
sizeable numbers having similar characteristics. FSWs belonging to cluster 2
had significantly high risk factors compared with Cluster 1. The overall
prevalence of HIV was 11.4% (10.6% in cluster 1 and 15.9% in cluster 2) among
high risk population. There exists a strong relationship between behavioral
patterns and HIV positive.
References
[1]
NACP (2012) Phase III State Fact Sheets. www.naco.gov.in
[2]
ANC (2011) HIV Sentinel Surveillance 2010 Bulletin. Strategic Information Management Unit, APSACS, Andhra Pradesh.
[3]
Chandrasekaran, P., Dallabetta, G., Loo, V., Mills, S., Saidel, T., Adhikary, R., Alary, M., Lowndes, C.M., Boily, M.C. and Moore, J., Avahan Evaluation Partners (2008) Evaluation Design for Large-Scale HIV Prevention Programmes: The Case of Avahan, the India AIDS Initiative. AIDS, 22, S1-S15. http://dx.doi.org/10.1097/01.aids.0000343760.70078.89
[4]
(2009-10) National Summary Report, Round-2. Integrated Behavioral and Biological Assessment.
[5]
Saidel, T., Adhikary, R., Mainkar, M., Dale, M., Loo, V., Rahman, M., et al. (2008) Baseline Integrated Behavioral and Biological Assessment among Most At-Risk Populations in Six High-Prevalent States of India: Design and Implementation Challenges. AIDS, 22, S17-S34. http://dx.doi.org/10.1097/01.aids.0000343761.77702.04
[6]
(2011) Guidelines for Surveys of Populations at Risk of HIV Infections. Integrated Behavioral and Biological Assessment. Define the Study Population. 9.
[7]
Mardia, K.V., Kent, J.M. and Bibby, J.M. (1980) Multivariate Analysis. Academic Press, London, 521 p.
[8]
Kleinbaum, D.G., Kupper, L.L. and Muller, K.E. (1988) Variable Reduction and Factor Analysis. Applied Regression Analysis and Other Multivariable Methods. PWS Kent Publishing Co., Boston, 595-640.
[9]
Aldenderfer, N.S. and Blashfield, R.K. (1984) Cluster Analysis. Sage Publication, Beverly Hills, 7-17.
[10]
SPSS Version 19.0, IBM, Armonk.
[11]
(2005-7) National Summary Report, Round-1. Integrated Behavioral and Biological Assessment.
[12]
Hemalatha, R., Hari Kumar, R., Venkaiah, K., Srinivasan, K. and Brahmam, G.N.V. (2011) Prevalence of & Knowledge, Attitude & Practices towards HIV & Sexually Transmitted Infections (STIs) among Female Sex Workers (FSWs) in Andhra Pradesh. Indian Journal of Medical Research, 134, 49-54.