(September 11, 2026) — PFAS, or per- and polyfluoroalkyl substances, are already in our food, water, and all our bodies. Since the 1940s, this group of compounds has been used in a multitude of consumer products from nonstick cookware to firefighting foam, construction materials, clothing, food wrappers, and even makeup. These manufactured chemical compounds have been dubbed “forever chemicals,” due to their slow breakdown process and ability to build up in both living things and the environment. Over the past couple decades, publicly available research has continuously indicated that PFAS and other forever chemicals are linked to a growing list of health problems. This includes hormonal interference, reduced immune response, increased risk of some cancers, increased risk of obesity, high blood pressure, high cholesterol, developmental effects in children, and notably, decreased fertility.
Infertility, a topic that continues to draw growing public attention, affects roughly one in seven US couples. Despite public awareness and the magnitude of the problem, there is still not a full nationwide picture that explores the reproductive consequences of PFAS exposure. Many existing studies have focused narrowly on a handful of older "legacy" PFAS compounds, leaving the effects of the newer PFAS that replaced them understudied.
Assistant Professor Xindi (Cindy) Hu has received a K01 Career Development Award from the National Institute of Environmental Health Sciences (NIEHS) for her project that aims to help close that gap. Her project, "A Place-Based Framework to Quantify Drinking Water PFAS Mixtures and Reproductive Health Risks," will provide half a million dollars in total funding over three years to deliver the first publicly available, national dataset estimating PFAS mixture exposures from drinking water and evaluating their impact on fertility outcomes using the world's largest web-based preconception cohort study.
Professor Hu's project builds on her earlier NIEHS-funded work modeling contamination in private wells. Using federal monitoring data, a 28-state public water supply dataset, and artificial intelligence (AI), her new project will construct a geospatial model of PFAS mixture exposure across the country. Then she will validate predictions made by the AI using available tap water data from the Nurses' Health Study and a separate citizen science project. Lastly, she will link those exposure estimates to fecundability (the probability of conceiving during a menstrual cycle) data from the Pregnancy Study Online, the world's largest web-based preconception cohort.
Professor Hu plans to share this common data source on the CAFE collection of the Harvard Dataverse in hopes that her research will enable other researchers beyond this project to pursue many new lines of inquiry across environmental health, epidemiology, and clinical research.