Exposure to endocrine disrupting chemicals via consumption of ultraprocessed foods: implications for maternal metabolic health in pregnancy

Michigan State University, East Lansing MI

Investigators

Abstract

PROJECT SUMMARY The average American obtains 47% of their daily calories from ultra-processed foods (UPFs), which include fast food, packaged desserts, salty snacks, frozen meals, and soft drinks. The links between UPF consumption and adverse human health outcomes has largely been attributed to the lower nutrient quality of UPFs. However, high-UPF diets may contain toxic endocrine disrupting chemicals (EDCs) used in/during food processing, preservation, and packaging. Thus, there is a critical need to determine if consuming diets high in UPFs increases the risk of adverse pregnancy outcomes and raises the body burden of EDC exposure in vulnerable populations. Addressing these important questions has been hampered by the labor-intensive nature of classifying the degree of food processing and lack of continuous and reliable measures of food processing. This study will use previously collected data from 483 women enrolled in the Illinois Kids Development Study (I-KIDS), a prospective pregnancy cohort from Champaign-Urbana, IL. We will apply FoodProX – a novel machine- learning algorithm that calculates a granular measure of food processing for the overall diet in a reproducible and scalable fashion – to characterize UPF consumption during pregnancy. Using previously collected high- quality dietary data, detailed biomonitoring of EDCs commonly found in food, and an array of maternal metabolic markers and neonatal outcomes, we will accomplish the following specific aims: 1) Estimate associations of UPF consumption during the first trimester with maternal insulin, glucose, cholesterols, lipids, and adipokines in mid- pregnancy; 2) Evaluate associations of UPF consumption during the first trimester with urinary or serum levels of phthalates, bisphenols, parabens, and perfluoroalkyl substances (EDCs) across pregnancy; and 3) Quantify the extent that EDC exposures mediate associations of UPF consumption with insulin, glucose, cholesterols, lipids, adipokines. The proposed study brings interdisciplinary expertise in environmental epidemiology, nutrition, machine learning, biostatistics, and big data to bear on this important topic. Successful completion of this proposal would provide the platform and capacity to examine the links between UPFs, EDCs, and human health during other life stages in I-KIDS and other cohorts we work with (e.g., HOME, MIREC, ECHO). Ultimately, the results of these studies would allow us to implement interventions to improve dietary quality during pregnancy and provide data to policy makers to regulate EDC exposures in food and update nutritional advice for pregnant women.