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An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Estimating lifetime risk from spot biomarker data and intraclass correlation coefficients (ICC)
1Human Exposure and Atmospheric Sciences Division, NERL/ORD, US Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA. pleil.joachim@epa.gov
Journal of Toxicology and Environmental Health. Part A
|August 29, 2013
Summary
This study introduces a statistical method to estimate long-term environmental exposures from single biomarker measurements. This approach aids in accurate risk assessment by converting spot biomarker data into average exposure distributions.
Area of Science:
- Environmental Health Sciences
- Biomarker Research
- Statistical Modeling
Background:
- Human biomarker measurements (blood, breath, urine) serve as personal environmental exposure surrogates.
- Biomarkers provide a temporal snapshot, while risk assessment requires long-term average exposure data.
Purpose of the Study:
- To develop a statistical method for estimating long-term average exposures from spot biomarker measurements.
- To enable risk assessment by comparing estimated individual means to biologically relevant risk levels.
Main Methods:
- Utilized intraclass correlations based on literature measurement variance components.
- Developed a three-tiered approach adaptable to varying metadata availability.
- Demonstrated methodology with urinary OH-pyrene data and generalized for other spot biomarker datasets (e.g., NHANES).
Main Results:
- A statistical approach was successfully developed and demonstrated for estimating long-term average exposures from spot biomarker data.
- The methodology allows conversion of spot biomarker data into estimated distributions of individual means.
- Provided spreadsheet-based examples for calculating population proportions exceeding biomonitoring equivalent levels.
Conclusions:
- The proposed statistical method effectively estimates long-term average exposures from spot biomarker measurements.
- This approach enhances environmental monitoring and risk assessment capabilities using readily available biomarker data.
- The generalized methodology is applicable to various biomarker datasets, facilitating broader public health research.
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