OBJECTIVE: We derived a clinical decision rule for determining which young children need testing for lead poisoning. We developed an equation that combines lead exposure self-report questions with the child's census-block housing and socioeconomic characteristics, personal demographic characteristics, and Medicaid status. This equation better predicts elevated blood lead level (EBLL) than one using ZIP code and Medicaid status. METHODS: A survey regarding potential lead exposure was administered from October 2001 to January 2003 to Michigan parents at pediatric clinics (n=3,396). These self-report survey data were linked to a statewide clinical registry of blood lead level (BLL) tests. Sensitivity and specificity were calculated and then used to estimate the cost-effectiveness of the equation. RESULTS: The census-block group prediction equation explained 18.1% of the variance in BLLs. Replacing block group characteristics with the self-report questions and dichotomized ZIP code risk explained only 12.6% of the variance. Adding three self-report questions to the census-block group model increased the variance explained to 19.9% and increased specificity with no loss in sensitivity in detecting EBLLs of ≥ 10 micrograms per deciliter. CONCLUSIONS: Relying solely on self-reports of lead exposure predicted BLL less effectively than the block group model. However, adding three of 13 self-report questions to our clinical decision rule significantly improved prediction of which children require a BLL test. Using the equation as the clinical decision rule would annually eliminate more than 7,200 unnecessary tests in Michigan and save more than $220,000.
OBJECTIVE: We derived a clinical decision rule for determining which young children need testing for lead poisoning. We developed an equation that combines lead exposure self-report questions with the child's census-block housing and socioeconomic characteristics, personal demographic characteristics, and Medicaid status. This equation better predicts elevated blood lead level (EBLL) than one using ZIP code and Medicaid status. METHODS: A survey regarding potential lead exposure was administered from October 2001 to January 2003 to Michigan parents at pediatric clinics (n=3,396). These self-report survey data were linked to a statewide clinical registry of blood lead level (BLL) tests. Sensitivity and specificity were calculated and then used to estimate the cost-effectiveness of the equation. RESULTS: The census-block group prediction equation explained 18.1% of the variance in BLLs. Replacing block group characteristics with the self-report questions and dichotomized ZIP code risk explained only 12.6% of the variance. Adding three self-report questions to the census-block group model increased the variance explained to 19.9% and increased specificity with no loss in sensitivity in detecting EBLLs of ≥ 10 micrograms per deciliter. CONCLUSIONS: Relying solely on self-reports of lead exposure predicted BLL less effectively than the block group model. However, adding three of 13 self-report questions to our clinical decision rule significantly improved prediction of which children require a BLL test. Using the equation as the clinical decision rule would annually eliminate more than 7,200 unnecessary tests in Michigan and save more than $220,000.
Authors: N Krieger; J T Chen; P D Waterman; M-J Soobader; S V Subramanian; R Carson Journal: J Epidemiol Community Health Date: 2003-03 Impact factor: 3.710
Authors: Bruce P Lanphear; Richard Hornung; Jane Khoury; Kimberly Yolton; Peter Baghurst; David C Bellinger; Richard L Canfield; Kim N Dietrich; Robert Bornschein; Tom Greene; Stephen J Rothenberg; Herbert L Needleman; Lourdes Schnaas; Gail Wasserman; Joseph Graziano; Russell Roberts Journal: Environ Health Perspect Date: 2005-07 Impact factor: 9.031
Authors: Anne Etchevers; Philippe Glorennec; Yann Le Strat; Camille Lecoffre; Philippe Bretin; Alain Le Tertre Journal: Int J Environ Res Public Health Date: 2015-12-03 Impact factor: 3.390