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Activity Number: 474 - SPEED: Infectious Disease, Environmental Epidemiology, and Diet
Type: Contributed
Date/Time: Wednesday, August 1, 2018 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #329275 Presentation
Title: A Weighted Kernel Machine Regression Approach to Environmental Pollutants and Infertility
Author(s): Zhen Chen* and Wei Zhang and Aiyi Liu and Germaine Buck Louis
Companies: NICHD/NIH and BBB/DIPHR/NICHD and BBB/DIPHR/NICHD and George Mason University
Keywords: Infertility; Kernel machine regression; PCBs; Pregnancy; Couple-based; logistic

In studying environmental pollutants in relation to human infertility, it is common that concentrations of a large number of exposures are collected in both partners. Such a couple-based study poses new challenges in analysis as these exposures may have complex non-linear and non-additive relationships with outcome. The kernel machine regression can be applied to model such effects while accounting for correlated structure within and across the exposures; yet it does not consider the partner-specific structure which may lead to suboptimal estimates. We develop a weighted kernel machine regression method (wKRM) to model the joint effect of partner-specific exposures where a linear weight procedure is used to combine partners' exposure concentrations. The wKRM reduces number of analyzed exposures and provides an overall importance index of female and male partner's exposures to infertility. Simulation studies demonstrate good performance of wKRM in both estimating the joint effects of exposures and fitting the infertility outcome. Application to a prospective infertility study suggests that male partner's exposure to PCBs might contribute more toward infertility.

Authors who are presenting talks have a * after their name.

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