An empirical comparison of lead exposure pathway models

Structural equation modeling is a statistical method for partitioning the v ariance in a set oi interrelated multivariate outcomes into that which is d ue to direct, indirect, and covariate (exogenous) effects. Despite this mod el's flexibility to handle different experimental designs, postulation of a causal chain among the endogenous variables and the points of influence of the covariates is required. This has motivated the researchers at the Univ ersity of Cincinnati Department of Environmental Health to be guided by a t heoretical model for movement of lead from distal sources (exterior soil or dust and paint lead) to proximal sources (interior dust lead) and then fin ally to biologic outcomes (handwipe and blood lead). The question of whethe r a single structural equation model built from proximity arguments can be applied to diverse populations observed in different communities with varyi ng lead amounts, sources, and bioavailabilities is addressed in this articl e. This reanalysis involved data from 1855 children less than 72 months of age enrolled in 11 studies performed over approximately 15 years. Data from children residing near former ore-processing sites were included in this r eanalysis. A single model adequately fit the data from these 11 studies; ho wever, the model needs to be flexible to include pathways that are not freq uently observed. As expected, the more proximal sources of interior dust le ad and handwipe lead were the most important predictors of blood lead; soil lead often had a number of indirect influences. A limited number of covari ates were also isolated as usually affecting the endogenous lead variables. The blood lead levels surveyed at the ore-processing sites were comparable to and actually somewhat lower than those reported in the the Third Nation al Health and Nutrition Examination Survey. Lessened bioavailability of the lead at certain of these sites is a probable reason for this finding.