Article citationsMore>>

G. M. Buck Louis, J. M. Weiner, B. W. Whitcomb, R. Sperrazza, E. F. Schisterman, D. T. Lobdell, et al., “Environmental PCB Exposure and Risk of Endometriosis,” Human Reproduction, Vol. 20, No. 1, 2005, pp. 279-285. doi:10.1093/humrep/deh575

has been cited by the following article:

• TITLE: Assessing Chemical Mixtures and Human Health: Use of Bayesian Belief Net Analysis

  AUTHORS: Anindya Roy, Neil J. Perkins, Germaine M. Buck Louis

  KEYWORDS: Bayesian Belief Network; Endometriosis; Environment; Mixtures; Polychlorinated Biphenyls

  JOURNAL NAME: Journal of Environmental Protection, Vol.3 No.6, June 21, 2012

  ABSTRACT: Background: Despite humans being exposed to complex chemical mixtures, much of the available research continues to focus on a single compound or metabolite or a select subgroup of compounds inconsistent with the nature of human exposure. Uncertainty regarding how best to model chemical mixtures coupled with few analytic approaches remains a formidable challenge and served as the impetus for the study. Objectives: To identify the polychlorinated biphenyl (PCB) congener(s) within a chemical mixture that was most associated with an endometriosis diagnosis using novel graphical modeling techniques. Methods: Bayesian Belief Network (BBN) models were developed and empirically assessed in a cohort comprising 84 women aged 18 - 40 years who underwent a laparoscopy or laparotomy between 1999 and 2000; 79 (94%) women had serum concentrations for 68 PCB congeners quantified. Adjusted odds ratios (AOR) for endometriosis were estimated for individual PCB congeners using BBN models. Results: PCB congeners #114 (AOR = 3.01; 95% CI = 2.25, 3.77) and #136 (AOR = 1.79; 95% CI = 1.03, 2.55) were associated with an endometriosis diagnosis. Combinations of mixtures inclusive of PCB #114 were all associated with higher odds of endometriosis, underscoring its potential relation with endometriosis. Conclusions: BBN models identified PCB congener 114 as the most influential congener for the odds of an endometriosis diagnosis in the context of a 68 congener chemical mixture. BBN models offer investigators the opportunity to assess which compounds within a mixture may drive a human health effect.