Abstract
INTRODUCTION: In an HIV/AIDS epidemic driven primarily by heterosexual transmission, it is important to have an understanding of the human sexual behaviour patterns that influence transmission. We analysed the distribution and predictors of within-partnership sexual behaviour and condom use in rural Zimbabwe and generated parameters for use in future modelling analyses. METHODS: A population-based cohort was recruited from a household census in 12 communities. A baseline survey was carried out in 1998-2000 with follow-up surveys after 3 and 5 years. Statistical distributions were fitted to reported within-partnership numbers of total, unprotected and protected sex acts in the past two weeks. Multilevel linear and logistic regression models were constructed to assess predictors of the frequency of unprotected sex and consistent condom use. RESULTS: A normal distribution of ln(sex acts+1) provided the best fit for total and unprotected sex acts for men and women. A negative binomial distribution applied to the untransformed data provided the best fit for protected sex acts. Condom use within partnerships was predominantly bimodal with at least 88% reporting zero or 100% use. Both men and women reported fewer unprotected sex acts with non-regular compared to regular partners (men: 0.26 fewer every two weeks (95% confidence interval 0.18-0.34); women: 0.16 (0.07-0.23)). Never and previously married individuals reported fewer unprotected sex acts than currently married individuals (never married men: 0.64 (0.60-0.67); previously married men: 0.59 (0.50-0.67); never married women: 0.51 (0.45-0.57); previously married women: 0.42 (0.37-0.47)). These variables were also associated with more consistent condom use. DISCUSSION: We generated parameters that will be useful for defining transmission models of HIV and other STIs, which rely on a valid representation of the underlying sexual network that determines spread of an infection. This will enable a better understanding of the spread of HIV and other STDs in this rural sub-Saharan population.