Predicting Childhood Lead Exposure at the Census Tract Level

Although lead exposure among U.S. children is declining, significant exposure and subsequent effects remain and harm children disproportionately in certain communities. The National Health and Nutrition Examination Survey (NHANES) estimates childhood lead exposure at a national level, but the data is insufficient for local programmatic decision-making. Identifying disproportionately affected communities remains difficult. State or local blood-lead surveillance data is not universally available; for example, seventeen states do not maintain blood-lead level (BLL) surveillance systems necessary to provide data to the Centers for Disease Control and Prevention. Thus, many U.S. communities have no BLL monitoring results, hindering efforts to reduce lead’s impact.

Combining the fitted regression model with readily available U.S. Census demographic predictor data provides predicted child BLL distributions at the census tract level for children of different ages or for populations at different points in time. These predictions provide a powerful quantitative tool for public health and housing officials and other stakeholders in childhood lead poisoning prevention. In particular, these distributions can be used to assess the number of children at risk in different parts of the urban area, which then can be used to help assess various intervention and resource allocation options. For example, the maps in the figure below provide predicted geometric mean BLLs at the census tract level for the Dallas/Ft. Worth area in Texas, along with census tract-level information on race (percentage Black), older housing (percentage built before 1960), and income level (percentage below the poverty level). By considering the demographic maps along with the BLL map, potential correlations can be considered at a useful level of geographic specificity when planning public health interventions or other types of actions.