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Related Experiment Videos

Temporal error in biomarker-based mean exposure estimates for individuals.

Scott M Bartell1, William C Griffith, Elaine M Faustman

  • 1Department of Statistics and Graduate Group in Epidemiology, University of California, Davis, California 95616, USA. smbartell@ucdavis.edu

Journal of Exposure Analysis and Environmental Epidemiology
|March 12, 2004
PubMed
Summary

Biomarker interpretation often assumes steady-state toxicant exposure, but this can cause errors. This study presents a statistical framework to quantify and understand this error for mercury exposure biomarkers.

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Area of Science:

  • Environmental Health
  • Toxicology
  • Biostatistics

Background:

  • Biomarker measurements at single time points are frequently used to estimate long-term toxicant intake.
  • Toxicant exposures are seldom at steady-state, are episodic, and vary in magnitude over time.
  • Biomarkers are most sensitive to recent toxicant exposures, complicating single-point interpretations.

Purpose of the Study:

  • To develop a statistical framework for evaluating the error introduced by the steady-state assumption in biomarker interpretation.
  • To provide guidelines for determining acceptable error levels and estimating potential errors.

Main Methods:

  • Developed a statistical framework to assess the magnitude of error from the steady-state fallacy.
  • Applied the framework to blood and hair mercury exposure biomarkers in human adults.

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  • Investigated the influence of exposure frequency, magnitude, duration, and inference duration on error.

    • Main Results:

    • The magnitude of error is dependent on various exposure factors.
    • Graphical representations illustrate error as a function of these factors, aiding biomarker interpretation.
    • A general approach for determining the mean and variance of temporal error was described.

    Conclusions:

    • The steady-state assumption in biomarker interpretation can introduce significant, quantifiable error.
    • The developed framework and graphical presentations offer valuable insights into interpreting mercury exposure biomarkers.
    • The study provides a method to evaluate errors from using steady-state models for time-varying exposures.