Journal Article

Using Community Science to Better Understand Lead Exposure Risks

Wood, Leah R., Filippelli, Gabriel M., Dietrich, Matthew, Krekeler, Mark P. S., Shukle, John T.

2022

Overview

Lead (Pb) is a neurotoxicant that particularly harms young children. Urban environments are often plagued with elevated Pb in soils and dusts, posing a health exposure risk from inhalation and ingestion of these contaminated media. Thus, a better understanding of where to prioritize risk screening and intervention is paramount from a public health perspective. We have synthesized a large national data set of Pb concentrations in household dusts from across the United States (U.S.), part of a community science initiative called “DustSafe.” Using these results, we have developed a straightforward logistic regression model that correctly predicts whether Pb is elevated (>80 ppm) or low (<80 ppm) in household dusts 75% of the time. Additionally, our model estimated 18% false negatives for elevated Pb, displaying that there was a low probability of elevated Pb in homes being misclassified. Our model uses only variables of approximate housing age and whether there is peeling paint in the interior of the home, illustrating how a simple and successful Pb predictive model can be generated if researchers ask the right screening questions. Scanning electron microscopy supports a common presence of Pb paint in several dust samples with elevated bulk Pb concentrations, which explains the predictive power of housing age and peeling paint in the model. This model was also implemented into an interactive mobile app that aims to increase community‐wide participation with Pb household screening. The app will hopefully provide greater awareness of Pb risks and a highly efficient way to begin mitigation. Plain Language Summary Community science has been gaining traction in many locales throughout the United States, particularly in the field of urban pollution. While this has helped with science education and informing communities of potential hazards and mitigation tools, little has been done to effectively assimilate this information in a useful way to help people in other communities throughout the country. Thus, we utilized a large data set of household dust samples provided by community scientists across the United States to build a simple predictive model that lets users know if their dust is likely to be high in a toxic metal, lead. Additionally, we built this model into an interactive mobile app that we plan to use as a recruitment tool for usage of lead screening kits. Ultimately, we plan to assess whether this mobile app improves user knowledge of household lead risks and increases participation from start to finish for free lead screening services. Key Points Community science sampling can provide national‐level insight Mobile apps can be utilized as a lead intervention tool Elevated lead in house dust can be reasonably predicted with a simple statistical model and two variables

• Publisher: John Wiley & Sons, Inc,John Wiley and Sons Inc,American Geophysical Union (AGU)
• Subject: Aerosols / Aerosols and Particles / Age / Atmospheric Composition and Structure / Biogeosciences / Community Engaged Research to Action: Examples From GeoHealth / Community involvement / community science / Composition of Aerosols and Dust Particles / Dust / Geochemistry / Geohealth / Health risks / Households / Housing / Ingestion / Inhalation / Lead / lead (Pb) / Lead content / Major and Trace Element Geochemistry / Marine Pollution / Megacities and Urban Environment / Metals / Natural Hazards / Oceanography: Biological and Chemical / Oceanography: General / Paleoceanography / pollution intervention / pollution remediation / Pollution: Urban and Regional / Pollution: Urban, Regional and Global / Prediction models / predictive modeling / Public Health / Questionnaires / Scanning electron microscopy / scanning electron microscopy (SEM) / Science / Urban environments / Urban Systems / Variables