A Bayesian High-Dimensional Couple-Based Latent Risk Model with an Application to Infertility

• Activity Number: 184
• Type: Contributed
• Date/Time: Monday, August 1, 2016 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Zhen Chen* and Beom Seuk Hwang and Germaine M. Buck Louis and Paul Albert
• Companies: Eunice Kennedy Shriver National Institute of Child Health and Human Development and Chung-Ang University and Eunice Kennedy Shriver National Institute of Child Health and Human Development and Eunice Kennedy Shriver National Institute of Child Health and Human Development
• Keywords: Chemical mixture ; Couple-based design ; Low dose additivity ; sub-additivity effect ; Latent class model

Abstract

Motivated by the Longitudinal Investigation of Fertility and the Environment (LIFE) Study that investigated the association between exposure to a large number of environmental pollutants and human reproductive outcomes, we proposed a joint latent risk class model with an interaction between female and male partners of a couple. This formulation introduces a dependence structure between the chemical patterns within a couple and between the chemical patterns and the risk of infertility. The specification of an interaction enables the interplay between the female and male's chemical patterns on the risk of infertility in a parsimonious way. We took a Bayesian perspective to inference and used Markov chain Monte Carlo algorithms to obtain posterior estimates of model parameters. We conducted simulations to examine the performance of the estimation approach. Using LIFE data, we found that in addition to the effect of PCB exposures on females, the male partners' PCB exposures play an important role in determining risk of infertility. Further, this risk is sub-additive in the sense that high chemical exposure is only required on one partner of the couple to determine the highest risk.