This study will address an important gap in knowledge for predicting which homes have high risks for lead exposure.

Sometimes the only way families learn if there are lead hazards in their home is when a young child that resides or spends a lot of time in that home has elevated blood lead levels. An investigation of the child’s sources of lead exposure often finds lead hazards in the home, and then actions are taken to eliminate those hazards.

Wouldn’t it be better if we could find more of those hazards before a problem showed up in a blood test? Lead risks can vary from house to house in the same neighborhood and are not based solely on the age of the house. This study will help better predict which homes may have lead hazards, so community organizations and government agencies (like state and local health departments or housing authorities) can provide households with information, testing, and recommendations to prevent exposures before lead can harm a family.

Study participants will collect samples of water, dust, and soil at their homes.

We are seeking your involvement volunteer sample collectors, to provide new data on lead in homes. Tests kits will be mailed to families living in study areas to collect dust, soil, and water samples for lead testing. We will integrate results from these tests with household and neighborhood information to improve our ability to predict which homes and neighborhoods have high lead exposure risks.

This is a three-year project that will create models and web-based maps to predict lead exposure risks. These models integrate machine-learning Bayesian networks with traditional fate- and transport models for lead. Preliminary research in rural North Carolina (NC) suggests that these models can accurately predict lead sources and occurrence in homes.

At the same time, this study will deliver insights on the effectiveness of lead hazard control interventions in homes that have fixed or taken actions to reduce lead.

Local, state, and federal resources are often used to find and fix lead hazards in the home. If you fixed your home for lead, your participation would help us learn about the effectiveness of current practices to reduce lead in protecting families from lead exposure and will help concerned communities and local, state, and federal governments better allocate resources to fix lead hazards in homes.

This program will also improve tools for communities to allocate resources for reducing home lead hazards.

Through this program, we will develop and share materials for training state and local decision-makers on the use of the new, integrated modeling platform. This can be used to help prioritize funding for home repairs and for communicating lead exposure risks in neighborhoods.

The study results will contribute to new valuable information about the various lead sources and lead risks in homes and neighborhoods nationwide.

Results of lead testing from individual household samples will be kept confidential and will not be shared with anyone outside the research team members from Indiana University, NC A&T, NCSU, and RTI International.

Study Areas for this Participatory Science Opportunity

The program includes six study areas:

North Carolina – Guilford County

Indiana – Allen, Marion, Delaware, St. Joseph, and Vanderburgh Counties

We are working in partnership with the following Lead Hazard Control Grantees: City of Greensboro, City of Fort Wayne, Indiana Housing and Community Development Authority.

Funding

This program is funded by a grant from the US Department of Housing and Urban Development (HUD) and is a collaboration between Indiana University, North Carolina Agricultural and Technical University, RTI International, and local partners in each of the study counties.

Press Releases

IU https://news.iu.edu/stories/2022/04/iub/releases/05-public-health-researchers-developing-predictive-tool-lead-exposure.html

NC A&T https://www.ncat.edu/news/2022/04/lead-study.php

RTI https://www.rti.org/announcements/public-health-researchers-developing-predictive-tool-household-lead-exposure.