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Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants

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...

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Autores principales: Sánchez, Brisa Ney, Hu, Howard, Litman, Heather J., Téllez-Rojo, Martha Maria
Formato: Texto
Lenguaje:English
Publicado: National Institute of Environmental Health Sciences 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060007/
https://www.ncbi.nlm.nih.gov/pubmed/21362588
http://dx.doi.org/10.1289/ehp.1002453
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author Sánchez, Brisa Ney
Hu, Howard
Litman, Heather J.
Téllez-Rojo, Martha Maria
author_facet Sánchez, Brisa Ney
Hu, Howard
Litman, Heather J.
Téllez-Rojo, Martha Maria
author_sort Sánchez, Brisa Ney
collection PubMed
description 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-log(e)-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–defined 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 p-values 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.
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spelling pubmed-30600072011-03-21 Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants Sánchez, Brisa Ney Hu, Howard Litman, Heather J. Téllez-Rojo, Martha Maria Environ Health Perspect Research 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-log(e)-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–defined 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 p-values 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. National Institute of Environmental Health Sciences 2011-03 2010-12-08 /pmc/articles/PMC3060007/ /pubmed/21362588 http://dx.doi.org/10.1289/ehp.1002453 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
spellingShingle Research
Sánchez, Brisa Ney
Hu, Howard
Litman, Heather J.
Téllez-Rojo, Martha Maria
Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
title Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
title_full Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
title_fullStr Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
title_full_unstemmed Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
title_short Statistical Methods to Study Timing of Vulnerability with Sparsely Sampled Data on Environmental Toxicants
title_sort statistical methods to study timing of vulnerability with sparsely sampled data on environmental toxicants
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3060007/
https://www.ncbi.nlm.nih.gov/pubmed/21362588
http://dx.doi.org/10.1289/ehp.1002453
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