CHEEC conducts vital research investigating cancer risk in collaboration with the Iowa Cancer Registry and researchers from across Iowa. This partnership leverages the extensive data collected by the Iowa Cancer Registry, a population-based cancer registry that has served the state since 1973, and is part of the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program. CHEEC researchers utilize these comprehensive cancer data to explore various factors contributing to cancer risk, including environmental exposures, lifestyle choices, and genetic predispositions. By analyzing biospecimens such as blood and urine, CHEEC aims to identify biomarkers and contaminants that may be linked to increased cancer risk. This research is crucial for understanding how different environmental contaminants, such as PFAS, neonicotinoids, fungicides, and metals, impact cancer incidence and progression. The collaboration with the Iowa Cancer Registry allows CHEEC to access detailed cancer incidence and survival data, enabling researchers to conduct robust epidemiological studies. These studies help identify trends and patterns in cancer occurrence, providing insights into potential risk factors and informing public health interventions. Through this partnership, CHEEC and the Iowa Cancer Registry are working together to advance cancer research, improve cancer prevention strategies, and ultimately reduce the burden of cancer in Iowa.

Ongoing Research: CHEEC is collaborating with researchers from the Iowa Cancer Registry and the University of Iowa Colleges of Medicine, Public Health, Engineering, and Liberal Arts to study the impact of environmental exposures, social determinants of health, and lifestyle choices on cancer rates in Iowa. The project uses secondary data related to the occurrence of environmental contaminants and their proximity to cancer cases. It employs spatial machine learning to analyze the interplay between cancer, pesticide use, social determinants of health, and lifestyle choices identifying high-risk clusters and geographic variations.