The purpose of testing for elevated blood lead levels (EBLLs) in children is to identify cases that would require appropriate treatment and/or environmental intervention. The 1989 Centers for Medicare & Medicaid Services requirement to test all children enrolled in Medicaid is costly and requires extensive outreach.1
It also created a need for clinical practice guidelines and decision rules to determine which young children are at high enough risk to require testing for lead poisoning.
In 1997, the Centers for Disease Control and Prevention (CDC)2,3
developed such clinical practice guidelines and defined high risk of symptoms of lead poisoning as having a blood lead level (BLL) of ≥10 micrograms per deciliter (μg/dL).4
CDC encouraged state health departments to develop plans to identify all children at high risk of lead poisoning based on local data concerning BLLs and selected risk factors.
The CDC guidelines were based on several criteria, including age of housing and percentage of population with incomes below the federal poverty level (FPL) in the ZIP code in which the child resides. As part of its targeting, CDC also recommended using information obtained from five self-report questions on lead exposure ().3
The Michigan Department of Community Health (MDCH) replaced question #5 with the following question: “Does the child's family use any home remedies that may contain lead?” and provided a list of such remedies. At the time, MDCH followed Medicaid rules requiring that all children enrolled in Medicaid be tested, although not all such children were actually tested. In addition, CDC and MDCH recommended that a child be tested if the child's caregiver answered “yes” or “I don't know” to any of the self-report questions, or if the child was Medicaid-enrolled or lived in a high-BLL-risk ZIP code.
CDC and MDCH recommended screening questions for pediatric lead poisoning
While these self-report questions have been widely used, studies have not found them to be good predictors of EBLL.5–8
Moreover, some of these questions are poorly worded and may not be understood by respondents. Therefore, there is a need to both improve the wording of these questions and assess the predictive validity of the improved questions.
Previous research in Michigan9
has led to a refined geographic approach to predicting the BLL of children. Unlike previous studies that use ZIP codes and census tracts, this research relied heavily on the characteristics of the census-block group (the smallest geographic unit for which detailed data were available). In Michigan, census-block groups explained substantially more variance in BLL than census tracts or ZIP codes. This method yielded a prediction equation with better sensitivity and specificity than ZIP code and Medicaid status, which would have identified more high-risk children, while saving more than $150,000 during the four-year period 2002–2005.9
This equation, derived from our previous work,9
predicted BLL from a weighted linear combination of the following characteristics of the census-block group in which the child lived: percentage of housing built before 1940 (HSNG_PRE1940), percentage of housing built during 1940–1949 (HSNG_1940-49), percentage of population with income <185% FPL (INC_185%_POV), percentage who did not graduate from high school (HS_DROPOUT), percentage black, and percentage Latino; as well as the following characteristics of the child: Medicaid status, race/ethnicity (BLACK_CHILD or not), age, and year tested.
The optimal prediction equation for 2002–2005 was Ln(BLL − 0.5) = −0.487 + 0.694 × HSNG_PRE1940 + 0.0119 × HSNG_1940-49 + 0.212 × INC_185%_POV + 0.400 × %_BLACK + 0.556 × %_LATINO + 0.206 × BLACK_CHILD + 0.172 × MEDICAID + 0.109 × MEDICAID × HSNG_PRE1940 + 0.171 × MEDICAID × HSNG_1940-49.
This prediction equation also includes coefficients of dummy variables that adjust for the child's age and year of the BLL test. Additionally, it includes empirical Bayesian residuals generated by Hierarchical Linear Modeling.12
These residuals estimate the degree to which the prediction equation over- or underestimates the BLL in each census-block group.
While prior literature suggests that these self-report exposure questions are not adequate predictors of BLL,5–8
it is possible that some of them are worth adding to the census-block group prediction equation. The present study expands our previous work by including modified MDCH-CDC self-report questions and other self-report questions suggested in the literature. The purpose is to create the most cost-effective method of targeting BLL testing, which can then be disseminated by public health professionals to clinicians and parents.