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

• Type of Material: Article
• Authors: Ritam Chowdhury, Emory University; Divyang Shah, Larsen and Toubro Limited; Abhishek R. Payal, Harvard Medical School
• Language: English
• Date: 2017-01-01
• Publisher: Medknow Publications
• Publication Version: Final Published Version
• Copyright Statement: © 2017 Indian Journal of Occupational and Environmental Medicine This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
• License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
• Final Published Version (URL): http://dx.doi.org/10.4103/ijoem.IJOEM_53_16
• Title of Journal or Parent Work: Indian Journal of Occupational and Environmental Medicine
• ISSN: 0973-2284
• Volume: 21
• Issue: 1
• Start Page: 2
• End Page: 8
• Keywords: Selection Bias; Healthy Worker Effect; Causal inference; Occupational Epidemiology
• Research Categories: Health Sciences, Public Health

Abstract

Known since 1885 but studied systematically only in the past four decades, the healthy worker effect (HWE) is a special form of selection bias common to occupational cohort studies. The phenomenon has been under debate for many years with respect to its impact, conceptual approach (confounding, selection bias, or both), and ways to resolve or account for its effect. The effect is not uniform across age groups, gender, race, and types of occupations and nor is it constant over time. Hence, assessing HWE and accounting for it in statistical analyses is complicated and requires sophisticated methods. Here, we review the HWE, factors affecting it, and methods developed so far to deal with it.