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Allostatic load scoring using item response theory.

Shelley H Liu1, Robert-Paul Juster2, Kristen Dams-O'Connor3

  • 1Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, United States.

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Summary
This summary is machine-generated.

This study introduces Item Response Theory (IRT) as a novel method for calculating allostatic load, identifying key biomarkers like BMI and CRP. IRT scores offer a more nuanced understanding of health disparities and depression compared to traditional sum-scores.

Keywords:
Allostatic loadBiomarkersDepressionItem response theoryNational health and nutrition examination surveyPsychometrics

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Area of Science:

  • Biomedical research
  • Health sciences
  • Methodology in health research

Background:

  • Allostatic load is typically measured using sum-scores of biomarkers, assuming equal contribution.
  • This equal weighting may not accurately reflect the varying importance of individual biomarkers.

Purpose of the Study:

  • To evaluate the traditional sum-score method for allostatic load.
  • To identify the most and least informative biomarkers for an allostatic load index.
  • To explore Item Response Theory (IRT) as an alternative method for calculating allostatic load scores.

Main Methods:

  • Utilized data from the 2015-2016 National Health Examination and Nutrition Survey (NHANES).
  • Applied Item Response Theory (IRT) models to twelve biomarkers of allostatic load.
  • Compared IRT-derived scores with traditional sum-scores in relation to socio-economic status and depression.

Main Results:

  • Body-mass-index and C-reactive protein emerged as the most informative biomarkers for allostatic load via IRT.
  • Both IRT and sum-score methods showed associations with lower socio-economic status and depression.
  • IRT scores demonstrated a stronger association with the impact of depressive symptoms on daily life.

Conclusions:

  • Item Response Theory (IRT) provides a data-driven approach to constructing allostatic load indices, accounting for biomarker informativeness.
  • IRT scores may offer enhanced sensitivity in detecting health effects and greater flexibility with missing data.
  • This methodological advancement holds potential for more refined analyses in health disparities and mental health research.