In order to be able to properly develop recommendations for fish consumption (species, portions, frequency), BTK inhibitor future studies must be directed toward the recognition of fish species and mass consumed (portion size) at the local level, and their possible contribution to the levels of Hg. When using the GLM, it is important before modeling to assess the correlation among the explanatory variables in order to avoid the effect of multicollineality and to get consistency in the fit models independent of the simplification procedures used [44]. The predictive power of the models fits solely for observations within the same range of data analyzed,

and should be assessed with validation tests using new, independent data [30]. Frequency of fish consumption contributed significantly

to explaining hair [THg]. However, based on the GLM, and considering the other significant co-variables (BMI and tobacco exposure) it explains only 43% of the [THg]. As the contribution of fish consumption frequency to [THg] is relatively low, it is necessary to assess other factors which may be contributing to exposure: selleck dental amalgams, use of creams to lighten the skin, and other factors that were not included in the present study. In particular, a more detailed assessment of the mass of the fish meal and type of fish (e.g., predatory) may prove as, or more, important than fish meal frequency. The GLM is a practical tool for identifying the variables that contribute to the explanation of the exposure to Hg during pregnancy. It allows for establishing the possible relationship between multiple potential sources of exposure and [THg] in hair of women in the prenatal period. The variables that were found in this study to have significant relationships with [THg] were hair segment sampled, BMI, tobacco exposure, and the ingestion of fish; which deserve a focused and intensive follow up at the physiologic and genomic

levels. In all models created, Suplatast tosilate the frequent ingestion of fish (more than once every two weeks) showed increases in the averages of the adjusted values of [THg]. [45], [46] and [47] This project was funded by grants from CONACYT–Salud (2010-C01-140272) and CIBNOR (PC2.0, PC0.10, PC0.5). This study would not have been possible without the assistance of some current and former members of the Wildlife Toxicology Laboratory and School of Fisheries and Ocean Sciences at the University of Alaska Fairbanks. University of Alaska personnel were partially supported through the Center for Alaska Native Health Research by Award Number P20RR016430 from the National Center for Research Resources and through the IDeA Network of Biomedical Research Excellence Award Number P20GM103395 from the National Institute of General Medical Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center for Research Resources or the National Institutes of Health.