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Healthy Worker Effect Phenomenon: Revisited with Emphasis on Statistical Methods - A Review.

Ritam Chowdhury1,2, Divyang Shah3, Abhishek R Payal4

  • 1Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA.

Indian Journal of Occupational and Environmental Medicine
|February 3, 2018
PubMed
Summary
This summary is machine-generated.

The healthy worker effect (HWE), a selection bias in occupational studies, varies significantly. This review examines factors influencing HWE and methods to address it in research.

Keywords:
Causal inferencehealthy worker effectoccupational epidemiologyselection bias

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Area of Science:

  • Occupational Epidemiology
  • Biostatistics
  • Public Health

Background:

  • The healthy worker effect (HWE) is a long-recognized phenomenon in occupational cohort studies.
  • It represents a form of selection bias, impacting health outcome assessments.
  • Its nature (confounding vs. selection bias) and impact remain subjects of ongoing scientific debate.

Purpose of the Study:

  • To provide a comprehensive review of the healthy worker effect.
  • To discuss the factors that influence the HWE.
  • To summarize methods for assessing and accounting for HWE in statistical analyses.

Main Methods:

  • Literature review of the healthy worker effect.
  • Analysis of factors influencing HWE variability.
  • Synthesis of statistical approaches for HWE mitigation.

Main Results:

  • HWE is not uniform; it varies by demographics (age, gender, race) and occupation.
  • The effect's magnitude can change over time.
  • Assessing and statistically managing HWE requires complex methodologies.

Conclusions:

  • Understanding HWE variability is crucial for accurate occupational health research.
  • Sophisticated statistical methods are necessary to address HWE.
  • Further research into HWE mitigation strategies is warranted.