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Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
Brisa Ney Sánchez, Howard Hu, Heather J. Litman and Martha Maria Tóllez-Rojo
Environmental Health Perspectives
Vol. 119, No. 3 (MARCH 2011), pp. 409-415
Published by: The National Institute of Environmental Health Sciences
Stable URL: http://www.jstor.org/stable/41203225
Page Count: 7
You can always find the topics here!Topics: Children, Pregnancy, Time windows, Health outcomes, Modeling, Regression analysis, Regression coefficients, Environmental health, Multiple regression, Missing data
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Background: Identifying windows of vulnerability to environmental toxicants is an important area in children's health research. Objective: We compared and contrasted statistical approaches that may help identify windows of vulnerability by formally testing differences in exposure effects across time of exposure, incorporating continuous time metrics for timing of exposure, and efficiently incorporating incomplete cases. Methods: We considered four methods: 1) window-specific and simultaneously adjusted regression; 2) multiple informant models; 3) using features of individual exposure patterns to predict outcomes; and 4) models of population exposure patterns depending on the outcome. We illustrate them using a study of prenatal vulnerability to lead in relation to Bayley's Mental Development Index at 24 months of age (MDI24). Results: The estimated change in MDI24 score with a 1-loge-unit increase in blood lead during the first trimester was -2.74 [95% confidence interval (CI), -5.78 to 0.29] based on a window-specific regression. The corresponding change in MDI24 was — 4.13 (95% CI, — 7.54 to — 0.72) based on a multiple informant model; estimated effects were similar across trimesters (p = 0.23). Results from method 3 suggested that blood lead levels in early pregnancy were significantly associated with reduced MDI24, but decreasing blood leads over the course of pregnancy were not. Method 4 results indicated that blood lead levels before 17 weeks of gestation were lower among children with MDI24 scores in the 90th versus the 10th percentile (p = 0.08). Conclusions: Method 2 is preferred over method 1 because it enables formal testing of differences in effects across a priori-denned windows (e.g., trimesters of pregnancy). Methods 3 and 4 are preferred over method 2 when there is large variability in the timing of exposure assessments among participants. Methods 3 and 4 yielded smaller/rvalues for tests of the hypothesis that not only level but also timing of lead exposure are relevant predictors of MDI24; systematic power comparisons are warranted.
Environmental Health Perspectives © 2011 The National Institute of Environmental Health Sciences