Predicting Blood-Lead Levels Among U.S. Children at the Census Tract Level

Abstract

Abstract Efforts to prevent childhood lead exposure are hindered by difficulty in predicting where exposure is concentrated in the absence of childhood blood-lead data. To help fill that gap, we created and validated a regression model to estimate childhood lead exposure in every census tract in the United States. Publicly available factors that were the most predictive of childhood blood-lead concentration were identified by a literature review and an evaluation of childhood blood-lead level (BLL) records from a public health surveillance program in Michigan (543,295 records for the years 1999–2009). The predictive power of the regression model was validated through a comparison to blood-lead surveillance program data from Massachusetts (833,951 records for the years 2000–2009), Texas (838,368 records for the years 1999–2009), and National Health and Nutrition Examination Survey (NHANES) datasets. The regression model identified percentage of pre-1960 housing, percentage of population below poverty line,...