There has been a paradigm shift in the manner in which the Health of the population is being currently viewed by health professionals & researchers. There is a realisation that the health of an individual is not just a function of his medical status but is also determined by the environment in which he work and lives. This idea of going beyond a pure bio-medical explanation for health status of individuals and looking at social determinants has provided researchers with tools for explaining the puzzle related to difference in health of individuals and societies who although living in the same country, state or municipal limits have different burden of disease. Research has identified various factors which influence the health status of the population. Analogously, there have been some studies to recognise the determinants of HIV. Variables that have been identified include Education (Alvarez-Uria, Midde, Pakam, & Naik, 2012; Bärnighausen, Hosegood, Timaeus, & Newell, 2010; Pais, 1996; Sarna et al., 2008; Vyas et al., 2009; Alvarez-Uria, Midde, & Naik, 2012), Socioeconomic status (Alvarez-Uria, Midde, Pakam, et al., 2012; Vyas et al., 2009), Alcohol (WHO, 2005), Employment (Alvarez-Uria, Midde, & Naik, 2012; Sarna et al., 2008), Wealth (Bärnighausen et al., 2010) & Rural v/s Urban Residence (Bärnighausen et al., 2010). However, the studies in India that looks at the pathway through which these social determinants act on HIV are scarce. This paper is an attempt to fill this gap. This study attempts to identify the pathway through which social determinants act on HIV morbidity in Women in the state of Kerala, India. Six independent variables that have been considered for this study include Health Service Delivery, Education, Employment, Wealth, Rural Residence and Alcohol. The sample size for the study is 677 women and the data has been drawn from the latest round of National Family Health Survey i.e. NFHS-3 which was conducted in the year 2005-06. Since there is presence of latent variable and multiple dependent and independent relationships in the conceptualised model, Structural Equation Modeling (SEM) has been employed. Both the direct as well as the indirect effect of each of the independent variables on HIV morbidity have been evaluated. The results reveal that Health Service delivery has the strongest determining influence on HIV morbidity. Also, there is almost no presence of any indirect effects of any of the variables in the model.
