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Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures
by
Li, Hesen
, Chen, Hua Yun
, Argos, Maria
, Turyk, Mary E.
, Persky, Victoria W.
in
Blood pressure
/ Chemicals
/ Computer Simulation
/ Environmental Exposure - analysis
/ Environmental Pollutants - analysis
/ Humans
/ Nutrition Surveys
/ Outcome Assessment, Health Care
/ Pollutants
/ Regression analysis
/ Sparsity
/ Statistical methods
2022
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Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures
by
Li, Hesen
, Chen, Hua Yun
, Argos, Maria
, Turyk, Mary E.
, Persky, Victoria W.
in
Blood pressure
/ Chemicals
/ Computer Simulation
/ Environmental Exposure - analysis
/ Environmental Pollutants - analysis
/ Humans
/ Nutrition Surveys
/ Outcome Assessment, Health Care
/ Pollutants
/ Regression analysis
/ Sparsity
/ Statistical methods
2022
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Do you wish to request the book?
Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures
by
Li, Hesen
, Chen, Hua Yun
, Argos, Maria
, Turyk, Mary E.
, Persky, Victoria W.
in
Blood pressure
/ Chemicals
/ Computer Simulation
/ Environmental Exposure - analysis
/ Environmental Pollutants - analysis
/ Humans
/ Nutrition Surveys
/ Outcome Assessment, Health Care
/ Pollutants
/ Regression analysis
/ Sparsity
/ Statistical methods
2022
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Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures
Journal Article
Statistical Methods for Assessing the Explained Variation of a Health Outcome by a Mixture of Exposures
2022
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Overview
Exposures to environmental pollutants are often composed of mixtures of chemicals that can be highly correlated because of similar sources and/or chemical structures. The effect of an individual chemical on a health outcome can be weak and difficult to detect because of the relatively low level of exposures to many environmental pollutants. To tackle the challenging problem of assessing the health risk of exposure to a mixture of environmental pollutants, we propose a statistical approach to assessing the proportion of the variation of an outcome explained by a mixture of pollutants. The proposed approach avoids the difficult task of identifying specific pollutants that are responsible for the effects and may also be used to assess interactions among exposures. Extensive simulation results demonstrate that the proposed approach has very good performance. Application of the proposed approach is illustrated by investigating the main and interaction effects of the chemical pollutants on systolic and diastolic blood pressure in participants from the National Health and Nutrition Examination Survey.
Publisher
MDPI AG,MDPI
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