Evaluating the proximate determinants framework for HIV infection in rural Zimbabwe.
- James JC Lewis (james.lewis{at}lshtm.ac.uk)
- Christl A Donnelly (c.donnelly{at}imperial.ac.uk)
- Geoff Garnett (g.garnett{at}imperial.ac.uk)
Abstract
Background:Risk factors for HIV infection can act at one of several causal levels, making interpretation of results problematic. One suggested solution has been a proximate determinants framework, analogous to that used in the study of fertility and child survival. In this framework, risk factors are grouped into "underlying", "proximate" and "biological" determinants.
Methods: A baseline, cross-sectional survey of HIV serostatus and potential risk factors was carried out among 9480 adults in Zimbabwe. Associations were assessed separately for men and women using logistic regression models; data were only included for those who reported sexual debut. The predictive ability of proximate determinants describing both individual and partnership characteristics was assessed along with the predictive ability of the underlying determinants. The significance of the underlying determinants once adjusted for proximate determinants was then evaluated. Finally the relationship between the underlying determinants and some of the key proximate determinants was explored.
Results: The two most important proximate determinants for both men and women were lifetime number of sexual partners and symptoms of sexually transmitted infections (p-values<0.001). After adjustment for all proximate determinants, some underlying determinants were still significant, particularly age group, marital status and community (p-values<0.001).
Conclusions: Whilst the proximate determinants could explain the action of many of the underlying determinants, several of the underlying determinants remained significant after adjustment for the proximate determinants. This suggests that the proximate determinants were not measured completely. One of the most important determinants of an individual’s risk of HIV infection is the HIV status of their sexual partners. This was not measured in this survey and may be related to the individual’s age (as a predictor for the age of the partner), marital status and community prevalence. Hence, partner’s HIV status will be measured in a subsequent survey of this cohort.
