Parcel-Level Data Improves Risk Prediction for Childhood Lead Exposure
Research By: Erika Manning, MS | Cole Brokamp, PhD
Post Date: January 22, 2025 | Publish Date: Jan. 22, 2025

Novel method developed at Cincinnati Children’s goes deeper than census tracts and postal codes to predict which children face elevated lead exposure risk
In many cities across the United States, old housing stock, low income and other factors can combine to increase a child’s risk of experiencing brain damage from environmental lead exposure. But routinely used screening tools based on neighborhood-scale risk factors can both over-predict risk for some residences within “high-risk” areas while overlooking high-risk residences in “low-risk” areas.
In a study published Jan. 22, 2025, in the Journal of Public Health Management and Practice, researchers at Cincinnati Children’s report developing a more accurate method for predicting lead exposure risk. The approach could help target educational and interventional resources more effectively to the places that need it the most.
Incorporating detailed housing characteristics like property age, condition, and proximity to lead sources can pinpoint high-risk areas for lead exposure at the level of individual properties. Integrating parcel-specific data into predictive models offers actionable insights for clinicians, families, policy makers, and public health advocates
Ongoing threat to child health
Lead exposure remains a threat to child health, contributing to developmental delays, behavioral problems, and lifelong challenges.
To prevent these harmful effects, a variety of health and housing policies and programs are intended to help reduce the numbers of children with blood lead concentrations that exceed 3.5 ug/dL, a reference value set by the Centers for Disease Control and Prevention (CDC).
Many states also mandate targeted lead testing. In Ohio, for example, children are screened for elevated blood lead concentrations based on a risk assessment of their residential ZIP Code.
The Power of Parcel-Level Data
This study used real-world data from nearly 28,000 blood lead screening tests involving children ages 6 and under to compare the predictive power of parcel-specific risk models against other methods that mixed neighborhood locations with various social and economic factors previously associated with increased risk for lead exposure.
Removing neighborhood-level characteristics and instead relying only on parcel- and source-level characteristics improved model accuracy and provided higher resolution insights about individual parcels that may not follow the pattern of other parcels within the same neighborhood.
Importantly, the parcel-level model uses existing data already collected for other purposes and did not require interactions with patients to collect new data. The model does not require new on-site property testing and does not rely on the limited accuracy of self-reported questionnaires.
Transformative Implications for Public Health
These findings will be of particular interest to clinicians, policymakers, and community advocates. More precise identification of high-risk homes means policymakers and community advocates can allocate resources more effectively, targeting and prioritizing the homes and neighborhoods that need it most. For clinicians, the model offers a practical tool to improve screening accuracy, enabling earlier detection and intervention for at-risk children.
What’s Next?
These findings highlight the importance of high-resolution spatial data, in this case detailed housing data at the property level. We are working to incorporate parcel-level risk factors into studies investigating other pediatric outcomes, including asthma and mental health, and are developing tools to help other researchers easily integrate property-level data into their analyses. We plan to operationalize a parcel-level risk assessment for screening and providing insights about lead exposure for children seen here at Cincinnati Children’s.
— Post authored by Erica Manning, MS
Don’t Miss a Post:
- Subscribe to the Research Horizons Newsletter
- Follow Cincinnati Children’s Research Foundation on Blue Sky: @cincyresearch.bsky.social
Original title: | Incorporating Parcel-Based Housing Conditions to Increase the Precision of Identifying Children with Elevated Blood Lead |
Published in: | Journal of Public Health Management and Practice |
Publish date: | Jan. 22, 2025 |
Research By


As a biostatistician, epidemiologist and geospatial data scientist, I specialize in informatics and machine learning, with applications to population-level environmental, community and health outcome data.