Environment/Climate Change
Investigating associations among perfluoroalkyl and polyfluoroalkyl substances (PFAS) levels and demographic characteristics within the Extremely Low Gestational Age Newborns (ELGAN) cohort. Kristina Stuckey* Kristina Stuckey Cailee Harrington Lauren Eaves T. Michael O’Shea Rebecca Fry
Perfluoroalkyl and polyfluoroalkyl substances (PFAS) are present throughout the environment and accumulate within water, food, and humans. PFAS exposure is associated with higher serum cholesterol, decreased immune function, higher risk of preeclampsia, and lower birth weight. Understanding demographic and social variables associated with higher exposure to PFAS can inform interventions for decreasing exposure. In this study, we investigated associations between socioeconomic and demographic variables and 4 PFAS: perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorohexanesulfonic acid (PFHxS) among 161 mothers who delivered babies in the Extremely Low Gestational Age Newborns (ELGAN) cohort from 2002-04. PFAS exposure was quantified in maternal blood spots taken during a perinatal window. Demographic variables include insurance type, use of food stamps, marital status, educational status, smoking during pregnancy, and hospital of birth, based on medical records and self-report. We also derived the Centers for Disease Control and Prevention’s Social Vulnerability Index (SVI) total percentile, based on reported residence during pregnancy. We assessed differences in PFAS exposure, both dichotomized and continuous, by key demographic variables using Wilcox and Kruskal-Wallis tests. A linear regression model was used to assess the relationship of SVI and PFAS exposure. Use of food stamps was associated with lower levels of PFOA (group mean 0.4428571 ng/ml and 0.1818182 ng/ml) and PFNA (0.471 ng/ml and 0.227 ng/ml) exposure. Increased social vulnerability was associated with lower PFNA exposure (Beta= 0.136, p-value= 0.096). Levels of all 4 PFAS differed based on the hospital of birth. Future analysis will include the incorporation of occupation data as well as investigate potential interactions of these variables.