A Cohort study evaluation of maternal PCB exposure related to time to pregnancy in daughters

Abstract

BackgroundPolychlorinated biphenyls (PCBs) remain ubiquitous environmental contaminants. Developmental exposures are suspected to impact reproduction. Analysis of mixtures of PCBs may be problematic as components have a complex correlation structure, and along with limited sample sizes, standard regression strategies are problematic. We compared the results of a novel, empirical method to those based on categorization of PCB compounds by (1) hypothesized biological activity previously proposed and widely applied, and (2) degree of ortho- substitution (mono, di, tri), in a study of the relation of maternal serum PCBs and daughter’s time to pregnancy.MethodsWe measured PCBs in maternal serum samples collected in the early postpartum in 289 daughters in the Child Health and Development Studies birth cohort. We queried time to pregnancy in these daughters 28–31 years later. We applied a novel weighted quantile sum approach to find the bad-actor compounds in the PCB mixture found in maternal serum. The approach includes empirical estimation of the weights through a bootstrap step which accounts for the variation in the estimated weights.ResultsBootstrap analyses indicated the dominant functionality groups associated with longer TTP were the dioxin-like, anti-estrogenic group (average weight, 22%) and PCBs not previously classified by biological activity (54%). In contrast, the unclassified PCBs were not important in the association with shorter TTP, where the anti-estrogenic groups and the PB-inducers group played a more important role (60% and 23%, respectively). The highly chlorinated PCBs (average weight, 89%) were mostly associated with longer TTP; in contrast, the degree of chlorination was less discriminating for shorter TTP. Finally, PCB 56 was associated with the strongest relationship with TTP with a weight of 47%.ConclusionsOur empirical approach found some associations previously identified by two classification schemes, but also identified other bad actors. This empirical method can generate hypotheses about mixture effects and mechanisms and overcomes some of the limitations of standard regression techniques.

Perinatal and Childhood Exposure to Cadmium, Manganese, and Metal Mixtures and Effects on Cognition and Behavior: A Review of Recent Literature

“…In the present mixtures literature, there is little consistency in terms of metals evaluated, measures of exposure used for each metal, and statistical approach employed for analyzing joint or interactive effects. Methodologies to address higher order mixtures such as weighted quantile sum regression [15] and Bayesian kernel machine regression [16] will help to address some knowledge gaps.…”

“…Because the number of possible chemical combinations is infinite, researchers must make choices when addressing the role of mixed exposure and health. The epidemiologic literature is now beginning to address lower-order interactions between metals, and new methodologies are being developed to address higher order mixtures [15, 16]. Understanding the health effects of combinations of metals, as well as metal interactions with other chemical and non-chemical exposures, is critical for progressing the field of environmental health and protecting children’s health [17].…”

Chemical mixtures and children's health

“…Further, when exposures are highly correlated, results from regression models can become unstable (22). To address these limitations, complex statistical methods have been suggested for estimating effects of multiple pollutants, including supervised clustering methods (e.g., tree-based methods, random forests), Bayesian approaches, dimension reduction approaches (e.g., principal component analysis)(24), and weighted quartile score regression strategies (25). Last, there is a lack of uniform terminology about interaction.…”

CO-occurring exposure to perchlorate, nitrate and thiocyanate alters thyroid function in healthy pregnant women

“…In the epidemiologic literature, analytical methods which typically evaluate associations with individual chemicals may not be appropriate to examine the effect of exposure to a chemical mixture on maternal thyroid function due to (1) correlated exposures, (2) low level exposures (particularly multiple compounds below an individual observable effect level, but which in combination produce an observable effect), and (3) differences in potency (i.e. chemicals with the highest body burdens are not necessarily the most potent/toxic) (Gennings et al, 2013). Weighted quantile sum (WQS) regression is an approach recently proposed to examine mixture effects in epidemiologic studies.…”