A Bayesian Model for Fecundability and Sterility

Abstract There is increasing evidence that exposure to environmental toxins during key stages of development can disrupt the human reproductive system. Such effects have proven difficult to study due to the many behavioral and biological factors involved in human reproduction. We analyze data from a North Carolina fertility study to assess the effect of prenatal, childhood, and current cigarette smoking exposure on fecundability and sterility. We use a mixture model that adjusts for timing and frequency of intercourse and allows both fecundability and sterility to depend on multiple covariates. We account for dependency among menstrual cycles within individual couples using a mixture density for a latent cycle viability variable. The mixture consists of a normal distribution describing heterogeneity among fecund couples with a point mass at 0 for sterile couples. The resulting distribution is more biologically plausible than the standard beta density. A Markov chain Monte Carlo scheme is used for Bayesian estimation of the model. There is some evidence that spontaneous intrauterine mortality results in decreased fecundability in subsequent cycles. Both current cigarette smoking and prenatal exposure of the woman to her mother's cigarette smoking are shown to be associated with a decrease in the probability of menstrual cycle viability.