Zhu, Jiali2018-11-162018-11-162018-12-01http://hdl.handle.net/2097/39335Polychlorinated biphenyls (PCBs) and dichlorodiphenyldichloroethylene (DDE) are endocrine disrupting chemicals which can imbalance the hormonal system in the human body and lead to deleterious diseases such as diabetes, irregular menstrual cycles, endometriosis, and breast cancer. These chemicals as environmental exposures still exist in the environment and food chains and can be accumulated in human fatty tissues for many years. These chemicals can also be passed from mothers to their children through placental transfer or breastfeeding; therefore, their offspring may be at increased risk of adverse health outcomes from these inherited chemicals. However, it is still unclear how the parental association with offspring health outcomes and the inter-generational phenotypic inheritance could be affected by these chemical compounds. In this study, we mainly focus on how PCBs and DDE can affect the inheritance of Body Mass Index (BMI) across generations, as BMI is the primary health outcome (or phenotype) linked to diabetes. We propose a biometrical inheritance model to investigate the effects of PCBs and DDE on the heritability of BMI over two generations. Technically, a linear mixed effects model is developed based on the decomposition of phenotypic variance and assuming the variance of the environmental effect depends on parental exposures. The proposed model is evaluated extensively by simulations and then is applied to Michigan Fisheater Cohort data for answering the research question of interest.en-US© the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).http://rightsstatements.org/vocab/InC/1.0/heritabilityPCBsDDEBMIBiometrical inheritance modelenvironmental exposuresA biometrical inheritance model for heritability under the presence of environmental exposures: application to Michigan fisheater dataReport